So ftw are Engine ering 10 IS51 - WordPress.com · • Formal transf orm ati on • I ntegr ati on fro m reusable com po nen ts S oci o-Tec hnic al Sy ste ms: • A system is a pu

So wtf are E ign ne re ing 01 IS51

SOFTW ERA ENG EENI R NI G

buS ject Co :ed 01 SI 51 I.A. Marks : 25 Hour /s W ee k : 40 xE am Hou :sr 30 Total Hou sr : 52 xE am Mark :s 1 00

AP RT – A TINU – 1 6 Hou sr

evO r iv ew: I tn ro ud c it o :n AF Q s' a ob ut software engineeri gn , Pro issef onal and et ih cal r se po isn b ili ty. Socio- eT chn ci al sys te sm : Em re ge tn s etsy m p or per it es; S tsy ems en nig eering; Orga zin atio sn , peop el na d computer s etsy m ;s Le ag cy s sy t sme .

TINU – 2 6 Hours Critical S sy t sme , S tfo ware Proc sse es: Critic la S etsy ms: A si pm le fas ety criti ac l ys ste ;m S sy te m dep ne dab ili t ;y Ava ali b ili ty and re il ab ili ty. oS ftwa er Proce sess : Mod sle , rP oce ss itera it on, rP o ec ss activ iti e ;s The Rational

Unified rP o ec ss ; Comp tu er Aided So wtf are Eng ni eer .gni

TINU – 3 7 Hou sr Requir eme nts: Softw ra e Requi er me tn s: Fu itcn onal and Non-functional requirem ;stne User er quirem ne ts; S tsy em requireme ;stn I tn erface specif ci ation; The so tf ware requi er m ne ts od cum .tne Requir eme nts nE gin ee r ni g Proc sse es: Feasib ili ty ts udies; Requirem stne e il c ati tion na d na alys ;si Requir me e stn va il datio ;n Requirem stne managem tne .

TINU – 4 7 Hou sr

syS tem mo sled , Project Manag me en :t S sy tem Mod le s: Co tn e tx mode ;sl Behavioral mode ;sl Data om d sle ; Ob ej ct mod sle ; rtS u tc ured me ht do s.

rP oj ce t Manag me ent: M na ageme tn ac it vitie ;s Proje tc plann ;gni Pro cej t sc eh duli gn ; iR sk m na ageme tn

TRAP – B

TINU – 5 7 Hou sr

oS ftwa er D ise gn: Arc tih e tc ur la De is g :n Arc tih ce t ru al de ngis decisio ;sn S tsy em or ag n azi tio ;n Modular deco pm o itis on st ly e ;s Co tn rol st ly es. 3 3 Object-Orien et d de is gn: Ob stcej and Ob tcej Cla ss e ;s nA Obje tc -Or tnei ed de is gn proc ;sse iseD gn evolu it on.

TINU – 6 6 Hou sr De lev o emp n :t aR p di So tf ware Devel po nem t: A elig method ;s E tx er me programmi gn ;

aR pid app cil ation developm tne . oS ftwa er vE olut oi n: rP ogram ve olu it on d ny amics; So awtf re ma tni ena ;ecn

Evolu it on rp oc sse e ;s Le ag cy s etsy m evolu it on.

TINU – 7 7 Hours Ve ir fic ta ion a dn Va adil tio :n eV rif ci ation and Va il da it no : Plann ;gni So wtf are sni p itce on ;s Automa et d ats t ci na alys ;si reV ifica it on and formal ohtem ds .

oS ftwa er testing: S sy tem test ;gni C mo ponent test ;gni eT ts ca es de ;ngis Test aut mo a it on . Dep ra tme tn of CSE, S BJ IT gaP e 1

S fo wt are E ign nee ir ng 10 SI 51

TINU – 8 6 Hou sr Ma an ge em nt: aM nagi gn People: Sele tc ing ts a ff ; Mo vit ating p oe ple; Managing p oe p ;el T eh Peop el aC pab ili ty Mat ru ity Model.

oS ftwa er Cost sE t mi at oi n: orP ud c it vit ;y Estimation et ch in que ;s Algor hti mic cost mod ile ng, rP o tcej ud r ita on na d st iffa ng.

eT xt oB ok: 1. I na Sommer :elliv So wtf are Eng ni ee r gni , 8th Edition, Pearson E ud cation, 20 70 . ( ahC pters-: 1, 2, 3, 4, 5, 6, 7, 8, 11 , 14, 1 ,7 21, 22 , 23 , 25, 26 ) R efe rence B oo ks: 1. Ro eg r. .S Pr sse man: So wtf are En nig eering-A Pract iti on re s appro ca h, 7th Ed iti on, Tata M Gc raw lliH , 2007. 2. P kna aj laJ ote: An I tn e rg ated pA proa hc to So wtf are Eng ni ee r gni , Wiley Indi ,a 2009.

Dep ra tme tn of CSE, S BJ IT Pa eg 2


AT BLE FO TNOC E STN

UNIT-1 Ov re view 4 - 5

S ico o-T ce hn ci al tsys ems 5 - 8

UNIT-2 Cr citi al S tsy ems , S fo wt a er Pro ssec es 9 - 51

UNIT-3 Re uq eri men st 1 6 - 20

Requi er men st nE g eni e nir g Proce ss es 2 0 - 21

UNIT – 4 S tsy e m m edo sl , Proje tc M na agement 2 2 - 27

UNIT – 5 Sof wt ra e D gise n, Ob ej ct-O eir nt de d ngise 28 – 94

UNIT-6 Developmen ,t Sof wt are Evolu it on 5 0 - 70

UN TI -7 Ve ir f a noitaci n V d alida it o , n oS ftw ra t e e its gn 7 1 - 93

UNIT-8 aM an gemen ,t oS f wt are Co ts itsE am noit 9 4 - 11 4



UNIT -1 O EV RV EI W

The ce onom sei of LA L develop de itan o sn era dep ne dent on so wtf ar .e M ro e and m ro e ys ste sm are so tf eraw contro ll ed.

So wtf are eng eni er gni si conce nr ed htiw theories, methods an d t oo sl for pro issef no al so tf ware developm tne .

sQAF bA o tu softwa er ne gine re ni g:

ahW t si software? So wtf are si set of Com up ter programs a ss o aic ted iw th docum tne a it on & conf gi ru a it on d ata ht at si n ee ded to make ht ese programs operate correc ylt . A so wtf are s tsy em cons stsi of a nu bm er of programs , conf gi uration lif es (u es d to tes up pro arg ms), ys stem document ita on d( escrib se eht st ur c ut re of eht s sy tem) na d u es r docum tne a it on

( xe pla sni how to use s tsy em .) So wtf are produc st may be d ve eloped for a par it cu al r cu ts omer or may be d ve eloped for a general mar tek . So wtf are produc st may be • Ge en r ci - developed ot be sold to a ra egn of differ tne cu ts omers • seB op ek (cu ts om) - developed f ro a is n lg e cu ts omer ca cord ni g

to ht eir spe ic ficati no

ahW t si software ne g ni eer ni g? So tf eraw eng ni ee r gni si an engineeri gn d si cip enil which si co cn erned htiw a ll

sa p stce of so tf eraw rp oduction . So tf eraw eng ni ee rs hs ould da po t a s tsy e am tic and orga in zed ap rp o hca to ht eir

work na d use a pp ropr tai e ot o sl na d tech in qu se dep ne di gn on ht e pr bo lem to be solved, ht e develo mp e tn co tsn ar stni and ht e er os u cr es ava ali b el .

ahW t si t eh id ff er ne ce betw ee n software ne g eeni r ni g and co pm ut re sc ei nce? Co pm u et r ics en ec si con ec rned iw th eht ory and nuf dam tne a ;sl software

en eenig ring si co cn erned w hti ht e prac it c ila ties of de lev po gni and de vil er gni useful so awtf re

Co pm u et r ics en ec ht e ro sei are cu rr tne ly insufficie tn to ca t as a c mo plete underpinni gn f ro so tf ware en nig eering

ahW t si t eh id ff er ne ce betw ee n software ne g eeni r ni g and sys tem engine re ni g? S tsy em eng eni er gni si concerned iw th a ll aspe stc of co pm uter-b esa d s etsy ms

develo mp tne ni clud gni ah rd aw r ,e so wtf are and p or c sse en nig eering. So awtf re en eenig ring si part of siht proc sse

S tsy em eng eni ers are invo evl d ni s tsy em sp ce ification, arch ti e tc ru al d ise gn, tni egration na d deplo my ent

ahW t si a software rp o ec ss ?

A set of ca ivit ties whose goal is eht d ve elop tnem or ve olu it on of so tf wa er Ge en ric act ivi ties ni lla so wtf are proce sess a er : • Spe ic fi ac tion - w ah t eht s sy tem hs ould do na d sti d leve opmen t co sn tr tnia s • D leve op nem t - p or ud c it on of eht so wtf are tsys em Dep ra tme tn of CSE, S BJ IT Pa eg 4

S fo wt are E ign nee ir ng 10 SI 51 • ilaV da it on - ehc ck gni that eht so awtf re si hw at the cu ts omer tnaw s • Evolu it on - c ah n ig ng ht e so awtf re ni re ps o sn e to hc ang gni demands

ahW t si a software rp o ec ss mode ?l A mis p il fied repr se e atn tion of a so tf ware pro ec ss , rp ese tn ed rf om a sp ce if ci perspect vi e Exa pm les of rp oce ss persp ce sevit ra e • W ro lfk ow perspect vi e - es uq en ec of ca it vities • D ta a- lf ow persp ce evit - fni orma it on lf o w • Role a/ c it on persp itce ve - who od es hw at

eneG r ci proce ss mod sle • Wa et rfa ll • Evolu it onary d ve elopme tn • Formal tr sna rof m ita on • tnI egr ita on f mor reusab el com op tnen s S ico o-T ce hn ci al S etsy ms: • A s sy tem si a up rposeful co ll ce tion fo ni ter-rela et d com op stnen w ro ik ng to eg ther

towards some co mm on bo ej c vit e. • A s sy tem may inc ul de so wtf are, me hc a cin al, le ce tri ac l and ele ctro in c ah rd aw re

and be po are et d by people. • S tsy em compo stnen era depende tn on other s tsy em co pm o nen ts

T eh proper seit and behavior of s etsy m compo nen ts ra e ni extr aci bly i tn er-m ni gled

rP o lb e sm of sys te sm engin ee r ni g • L ra ge s etsy ms are usually designed to so evl 'wicke 'd p or blem s • S tsy ems eng ni ree ing re uq ir se a gr ae t deal of co-ord ni ation acro ss d si cip nil es

• A ml o ts i fn ini te po iss b ili t sei for d ise gn trade-o sff ac or ss co pm onents • Mutual d tsi ur ts and al ck of underst na ding acro ss e eenign ring d si ciplines

• S tsy ems mu ts be d ise g en d ot sal t many years ni a changing environm ne t

oS ftwa er a dn sys te sm ne g ni eer gni The p or op itr on of so awtf re ni sys et ms si incr ae s gni . So wtf are- rd vi en gener la pu pr ose le ce t nor ics si replac gni sp ce ial- up pr o es sys t me s orP ble sm of s sy tems e enign er gni ra e mis i al r ot p or ble sm of so awtf re eng eeni ring

So wtf are si s ee n sa a pr bo lem ni s tsy ems engi een ri gn . aM ny al r eg s sy tem pro ej c st have b nee d le ayed be ac use of soft aw re p or b el ms.

remE gent rp operties • rP oper it es of eht system sa a hw ole ar ther ht an p or pert sei taht can be d re evi d rf om

ht e proper seit of co pm one stn of a s tsy em


S fo wt are E ign nee ir ng 10 SI 51 • mE e gr e tn pr po er it es are a co sn equ ecne of eht r ale tio sn hips b ewte en s tsy em

co pm onents. They c na ther fe ore o yln be ssa es es d and meas ru ed o ecn ht e co pm onents ha ev be ne getni r ta ed tni o a metsys .

xE a pm l se fo me erg tne properti se 1. The overall we gi ht of the tsys em • T sih si an e ax pm el of na emerge tn prop re ty that ac n be pmoc uted rf om ni dividu la com op ne tn p or per seit . 2. The re il ab ytili of the sy ets m • T sih depends on eht re ail b ili ty of s sy tem com op nen ts and eht relationships be ewt en ht e compone stn .

3. The u as b tili y of a tsys em • T sih si a complex property ihw ch si not is mp yl depend tne on eht s sy tem hardware na d so tf wa er ub t sla o dep ne ds on eht s tsy em po er ta ors na d the environme tn hw ere ti si u es d.

pyT es of emergent rp operty

1. Func it onal pr po er it es • The es a pp ae r when a ll t eh par st of a metsys w ro k toge eht r to a ihc eve some ob ej c vit e. For exa pm l ,e a bicycle has ht e f nu c it no al pr po re ty of being a t ar nsport ita on d cive e once ti has be ne a ss e bm led f mor sti comp no ents . 2. Non-func it o lan emerge tn proper it es • Exa pm sel are r aile b ili ty, perf mro ance, fas ety, and security. The es r le ate to eht behavi ruo of eht s etsy m ni its opera it onal e ivn ronme tn . hT e y are o tf en critic la for com up t re -b sa ed s etsy ms as fa li ure to a ihc e ev some min mi al de nif ed level in ht e es pr po er it es may make t eh s etsy m unu as ble.

eB ac use of compone tn i tn re -dep ne denc sei , fau stl c na be p or p ga ated rht ou hg the

ys stem S etsy m af li ru es o tf en occ ru b ce au es of u fn or ese en i etn r-relations ih ps be wt een Co pm onents tI si p or bab yl impo iss ble to a itn cipa et lla po iss ble compone tn r le ationships So wtf are re il ab ili ty measures may evig a fa sl e pict ru e of eht ys stem er ail b ili ty

syS tem re il a lib ity eng ni e gnire 1. Hardwa er re il abil yti • hW at si ht e p or bab ili ty of a ah rdware c mo op ne tn fa ili ng and how lo gn od es it take ot rep ia r ht at com op nen t?

2. Sof wt are ailer b ili ty • How kil ely si ti that a soft aw re co pm one tn w lli pro ud ec na cni orr ce t uo t up t. So wtf are fa li ru e si usu la ly d si t tcni f mor ah rdware fa li ure ni t tah so awtf re does not wear out. 3. Op re ator re il ba i ytil • How kil ely si ti that t eh operator of a tsys em wi ll m ka e an e rorr ? Influenc se on r aile b ili ty Dep ra tme tn of CSE, S BJ IT Pa eg 6

S fo wt are E ign nee ir ng 10 SI 51 Re il a ilib ty er la it o sn h spi 1. Ha dr ware fa li u er c na gener eta spur oi us gis na sl taht are ou ist de t eh range of ni pu st xe p ce et d by the so wtf are

2. So tf ware rre ors ac n ac use a al rms to be ac it vated ihw ch cause po era ot r str sse and el ad ot operator er or rs

3. T eh envi or nme tn ni w hcih a s tsy em si in ts alled can affect sti re il ab ili ty

syS te sm and their e vn iro emn nt S etsy ms are not ni dep ne d tne ub t tsixe in an en iv or mn ent S etsy ’m s f nu ction may be to c ah nge its en iv or mn ent. E ivn ronme tn af ef cts eht fu cn tio in gn of eht s sy tem .e g. s sy tem m ya er quire e el ctrical su pp ly from sti en iv ronment The orga azin tional sa well as ht e p yh si ac l en iv or nmen t may be i pm ro tant

Human a dn o gr a sin at noi al fa tc o sr

rP oc sse c ah nges • Does ht e sys et m requi er cha segn to ht e ow rk proc sesse ni the en iv ro mn ent? J bo cha gn es • Does ht e sys et m de- lliks the users ni an en iv ronme tn or cause eht m to change eht way they work?

rO gan si a it onal chang se • Does ht e sys et m chan eg eht po itil cal op wer rts ucture ni na organ si ation?



syS tem a cr hitecture mode ll ing nA cra h ti ce tu ar l dom el pr se e stn an ab ts ract eiv w of eht s bu -s tsy e sm ma ik ng up a

ys stem may ni clude m ja or informa it on lf ows be wt e ne sub-s sy tems I sU ually pr se ented as a block diagram I M ya identify d effi re tn types of func it on la co pm onen t ni t eh om del

syS tem ve olut noi aL rge s tsy ems have a lo gn fil etime. They um ts ve o evl to me te chan ig ng requi er m tne s

Evolu it on si in eh ren lt y co ts ly • hC a gn es mu ts be a an lysed from a et c inh cal and bu ssenis persp ce it ve • Sub-s tsy ems etni r ca t so u nan ticipated pr bo lems c na ar esi • There si r era yl a ra it ona el for or nigi al de is gn dec isi on s • S sy tem ts ru tc ru e si co rr pu ted as ahc n seg are made ot ti Ex si t gni sys tems w ih ch must be ma tni a ni ed are somet semi ca ll ed gel acy sys tems

The s sy tem eng ni ee r gni pro ssec

sU ually fo ll o sw a ‘waterfa ll ’ model b ce au es of the en ed for par lla el developm tne of d ffi ere tn par st of ht e s sy tem • elttiL scope of r ti re ita on b wte e ne pha ses b ce ause ah rdware hc anges are ev ry expe visn .e So wtf are may ha ev to compe tasn e for ah rd aw re p or b el m s

Ine iv tably vni o vl es engineers from d effi rent d si cip senil who mu ts work toge ht er • Mu hc sc po e for m si und re ts and gni eh re. Differe tn d si cip senil use a d ffi ere tn vo ac bulary and mu hc nego it a it on si re uq ired. Eng ni e re s may ha ev persona l ga endas to fu llifl .



NU IT-2 CRITI LAC SYST ME S, SOF WT AR E PROC SE ES S

C itir ca l S etsy ms • F ro rc iti cal s tsy ems, ti si usu la ly the sac e that eht mos t pmi or tnat s sy tem p or perty

si t eh dependab ili ty of ht e s sy tem . • T eh dependab ili ty of a s sy tem r lfe ects eht u es ’r s d ge r ee of rt u ts ni that s tsy em. I t

re lf e stc the txe e tn of ht e u es r’s co ifn den ec that it lliw po erate sa users xe p ce t and aht t ti will not ‘fa li ’ ni normal u es .

• U fes u nl e ss and rt u owts r niht e ss are not eht as me iht ng. A s tsy em does not have to

be rt u ts ed to be useful Dime isn o sn of de dnep a lib ity

hT e s tfo wa er pro ec ss A so wtf are pro ec ss si a ts ructured set of ac ivit t sei requi er d to d ve elop a software ys stem

tI invo sevl t eh fo ll ow gni phases:

• Spe ic fi ac ti no • D ise gn • ilaV da it on • Evolu it o n A so wtf are pro ec ss m do el si na ab ts r ca t repr tnese a it on of a proc sse . It pr se e stn a d cse rip it on of a proc sse from some par it cu al r perspe evitc .

oS ftwa er proce ss mode sl 1. T eh water llaf om d le • eS para et dna d itsi nct pha ses of sp ce ification and d leve opme tn 2. Evolu it o an ry d ve elopment • Spe ic fi ac tion an d d leve opment are etni r el a ev d Dep ra tme tn of CSE, S BJ IT Pa eg 9

S fo wt are E ign nee ir ng 10 SI 51 3. oF rm la s tsy ems developme tn • A ma ht e am ti ac l s tsy em dom el si f mro ally t ar fsn ro m de to na mI plementati no

4. Reuse-b sa ed develo mp tne • The s etsy m si assemb el d rf om e six ting com op tnen s Wa ret f lla mo ed l

The d fi fere tn p ah s se in waterfa ll m do el are :

• eR quirem stne analys si and de inif tion • S tsy em an d so wtf are de gis n • mI p mel entation na d u tin te its ng • I tn egra it on and tsys em set ting • Ope ar it on na d ma tni enance

The dr wa back of the aw et rfa ll model si ht e di ff ci ulty of accommod gnita cha gn e a tf er ht e

proc sse si underway. W ta e fr a ll om del rp ob smel • Infle ix ble par itit oning of ht e proje tc ni to d tcnitsi ts age s

• T sih makes ti di ff ci u tl to re ps ond to hc ang ni g cu ts om re r qe uir me ents

T sih om d le si only appropriate when the re uq ireme stn are we ll -understo do .

vE o ul tiona yr de lev o emp nt

hT ere are 2 typ se : 1. Explo tar ory developm tne

Dep ra tme tn of CSE, S BJ IT P ga e 10

S fo wt are E ign nee ir ng 10 SI 51 • Obje vitc e si to work htiw cu ts omers na d to evolve a nif al s etsy m from na initial out enil

specification. Should ats rt w hti ew ll-under ots do er uq eri me tn s 2.Th or w-away p or totyping • Obje vitc e si t o underst na d ht e s sy tem requirements. ohS uld start

with poor yl under ots od requirem ne ts

orP b el ms • aL ck of rp o ec ss isiv b ili ty • S sy tems are o tf en p roo yl ts ru tc ur de • Spe ic al ski sll (e.g. ni la gn uages for rapid p or totyping) may be re uq ired App acil b ytili

• For ms a ll ro medium- zis e ni t re active s tsy em s • For par st of large s sy tems .e( g. eht user ni terface) • For hs ort- fil etime s sy tem s Formal sys et ms develo mp ent tI si b sa ed on eht tr na sf mro ation of a ehtam ma cit al sp ice fication ht rou hg diff re e tn

re rp nese tati no s ot na e ex cutable prog ar m. Tr fsna mro a it o sn are ‘co rr ssentce -pr se er iv ng’ s o it si ts ra fthgi orw ra d to hs ow ht at the program co fn or sm to sti spe ic f aci tion. tI si em ob d ei d ni eht ‘ lC ean moor ’ appro ca h to so awtf re d ve elopme tn .



elborP m s • N ee d f ro sp ce ia sil ed sk slli and train gni to pa p yl ht e technique • D fi ficu tl to of rm la ly spe ic fy some aspe stc of ht e system such as

ht e user tni re af ec Ap lp aci b ytili • Cr iti cal s tsy ems se p ice ally tho es hw ere a efas ty or es curity case

mu ts be made before the s tsy em si p tu ni t po o re ita no Reuse-o ir ented ed lev opmen t tI si b sa ed on s sy temat ci reu es ehw er sys et ms ra e ni tegrated from e gnitsix

com op nents or OC TS ( oC mmercial-o ff -the- hs e fl ) sys et ms L Pro ssec gats e s • Co pm o tnen anal sy is • eR uq irem stne mod ifi ac ti no • S sy tem d ise gn iw th reus e • D leve op nem t na d ni tegrati no T sih ap rp oach si b ce mo ing more mi porta tn ub t llits il mited experie cn e with it

Pro ssec ti era it no S etsy m er quireme stn AL YAW S evo vl e ni the cou sr e of a proje tc os pro ec ss ti er ita on

hw ere ae r eil r gats es are reworked si wla a sy part of eht proce ss for al r eg s sy tems etI r ita on can be pa p il ed ot any of ht e generic proc sse m do els

wT o (rel ta de ) a rpp ao ches

• nI cremental developm tne • Spir la de lev o mp e tn Incremental deve ol mp en t

taR h re ht an de vil er the s etsy m as a s ni gle d le ivery, eht d ve elopme tn and delivery si broken down tni o ni erc ments iw th each increm tne de evil ring part of eht re uq ired fu cn tiona il ty.

sU er requirements are pri ro esiti d and ht e ih ghe ts rp iority requirem stne are ni clud de ni early cni rements .

nO ce the d ve elopment of na cni reme tn si star et d, eht requirem stne era froz ne thou hg requirem stne for later cni reme stn ac n co nitn ue to ve olve. Dep ra tme tn of CSE, S BJ IT P ga e 12

S fo wt are En ig nee ir ng 10 SI 51

Adva tn ages

• Cu ts mo er lav ue nac be de evil red iw th each ni cremen t so s etsy m func it ona il ty si ava ali b el earlier

• Ear yl ni creme stn ca t as a prototype to help ile cit

re uq irem stne for later ni creme tn s

• Lower r ksi of overa ll pro ej ct fa li ure

• The h hgi e ts rp iority s sy tem es vr ic se t ne d ot re ec evi t eh mo ts itset ng

pS ri al d ve e ol mp en t rP o ec ss si rep er se tn ed as a spi ar l r hta re ht an as a se uq ence of ivitca ties with

b tkca racking E hca l oo p ni eht spiral repre stnes a p esah ni the pro ssec . No xif ed p sesah su hc as specific ita on or de ngis -loops ni ht e spiral are hc osen depending on what si required.

iR s sk are xe plici lt y asse ss ed na d r se o vl ed ht uor hg out eht pro ec ss .


S fo wt are E ign nee ir ng 10 SI 51 C SA E Co pm u et r- ia d de so awtf re eng eeni ring (CASE) si soft aw re to us pport so tf wa er d ve elopm tne na d ve olution proc sse es. Ac it vity automa it o n • G ar p ih cal ed ti ors for s tsy em mod le developm tne • D ta a dic it onary to manage d ise gn e itn ties • G ar p ih cal IU bu li d re of r user tni er caf e co sn truc it on • De ub gg ers to us ppo tr program fau tl nif ding • Auto etam d tr na slat ro s to neg erate new v re sio sn fo a rp ogram

esaC t ce hnology esaC t ce hnology has led ot significa tn impro ev me stn ni ht e sof wt are proce ss ht ou hg

no t ht e order of ma ting ude mi pro ev m stne that were o ecn pred tci ed

• Sof awt re eng eni er gni requi er s crea evit th uo hg t - th si si not readily automa at ble • Sof awt re eng eni er gni si a team ac it vity and, for lar eg proje stc , mu hc it me si sp tne ni t ae m tni eractio sn . CASE et chnology do se not re la ly sup op rt seht e

AC SE cla iss f aci tion

lC assifi ac tion h le ps us under ts an d eht d ffi ere tn typ se of SAC E ot o sl and ht eir s pu p ro t for proce ss itca vities. 1. Func it onal p re sp ce vit e • oT o sl are salc s ifi ed a cc ro d gni to ieht r specif ci fu cn ti no 2. rP o ec ss perspect vi e • oT o sl are salc s ifi ed a cc ro d gni to pro ssec a itivitc es ht at are us ppor det 3. I tn egra it on p re spect vi e • oT o sl are salc s ifi ed a cc ro d gni to ieht r ro ag nisa it on tni o tni egra et d u tin s

AC SE tni eg ar tion

oT o sl • Support ni d ivi ud al proce ss ta sks such as de ngis co tsisn ency chec ik ng, txet ed iti ng, te c.

Workbe hcn es • Support a proce ss p esah su hc as spe ic f ci ation ro d ise gn, oN mr ally ni clude a number of tni egr ta ed ot ols E ivn or nme tn s • Support lla or a sub ts antial part of an itne er soft eraw rp oc sse . Normally ni clude se ev ar l i tn e rg a et d workbenche s Dep ra tme tn of CSE, S BJ IT P ga e 14

S fo wt are E ign nee ir ng 10 SI 51 Too sl , workbe hcn es, envi or mn ents



TINU -3 R RIUQE E EM NTS

eR quirem tne s

eR quirem tne - Descrip it o sn na d spe ic f ci atio sn of a s tsy em.

eR quirem stne eng ni ee r ni g • T eh pro ssec of tse ab il s ih ng ht e ser civ es ht at the c tsu o em r re uq ir se f mor a s etsy m

and eht co tsn ra ni ts under w ih ch it operates and si d ve eloped. • T eh requirem stne the sm e vl es are ht e d se rc ip it o sn of ht e sys et m ser iv c se and

co tsn raints ht at are gen are et d during the er quire stnem engin ee ri gn pro ssec .

eR quirem tne : A requireme tn may range from a ih gh-le lev ab ts ract st ta em tne of a servi ec or of a tsys em co tsn ra tni to a deta li ed mathema it ac l functi no la spe ic fic ita on.

eR quirem stne serve a du la func it on : • May be eht ba sis f ro a bid f ro a co tn ra tc - ht er fe ro e mu ts be op ne to tni re p er at tion • May be eht ba sis f ro the co tn r tca sti e fl - ht er fe ore mu ts be d nife ed ni d te a li • Bo ht ht ese ats t me e stn may be c lla ed re uq irem ne ts

nuF ctional and non-fu cn tional iuqer r eme nts D fe initions Func it onal requirements : S at teme stn of s re iv ces ht e s sy tem s oh uld pro iv de, how eht ys stem shou dl re ca t t p o ar cit u al r ni up ts na d how ht e s sy tem s oh uld b he ave ni

par it cul ra tis ua it o sn . Non-func it onal requirem stne : Co tsn rai stn on ht e es r iv ces or fu itcn ons o ff ered by t eh ys stem su hc sa it ming co tsn ra ni ts, co sn tra stni on the d ve elo mp e tn pro ssec , ts anda dr ,s te c.

Do niam requi er ments : Requireme stn ht at come rf om ht e app il cation domain of ht e ys stem and ht at er lf ect c ah racter si tics of ht at dom nia .

D te ai del de ircs ptions Func it onal requirements • They De cs ribe fu cn tionality ro s etsy m es r civ es • Dep ne d on ht e type of so tf ware, xe pe etc d u es rs a dn the type of system hw ere the

soft aw re si u es d • Func it onal u es r requireme stn may be ih gh-level ts a et ments of tahw ht e s sy te m

should do but func it onal system requireme stn hs uo ld de cs ribe eht ys stem serv ci es ni deta li


S fo wt are E ign nee ir ng 10 SI 51 Exa pm les (T eh re uq irem stne c na be de enif d as fo ll ow )s

• The user hs a ll be ab el to es ar hc eit eh r lla of ht e initial set of da at bases or sel ce t a subset rf om ti .

• The s sy tem sha ll pro iv de appropr tai e vie ew rs for eht u es r to r ae d docum stne ni ht e docum tne store.

• Every order hs a ll be lla ocated a u in que id itne fier O( RDER_ DI ) ihw ch the u es r sha ll be able to copy to eht a cc ou tn ’s permane tn ts or ega ar ae .

Non-func it onal requirem tne s

• They def eni s sy tem p or pert sei and co tsn r nia ts ekil re ail b ili ty, r se po sn e it me na d ts orage r qe ui er ments.

• Co sn tr nia ts are /I O d ive ce capab ili ty, system re rp se e tn a it no s, et .c • rP o ec ss re uq irem stne may a sl o be sp ce ified manda nit g

a pa citr ular SAC E s etsy ,m program gnim la gn uage or d leve opment me ht do Non-func it onal requirem stne may be m ro e critic la ht an fu cn tional requireme stn . If ht e es are not me ,t eht s sy tem b ce omes usele ss .

Non-func it onal classificatio sn 1. orP du tc requirem tne s

T eseh re uq irem stne specify t tah the d le i ev red p or ud ct mu ts beha ev ni a particular way e.g. xe ecu it on speed, re il ab ili ty, e ct . 2. Organi itaz onal er quire tnem s • eR uq irem stne which are a co esn qu ne ce of or ag n zi a it onal op il c sei and proc de ur se

g.e . proc sse st na da dr s u es d, mi plementation r qe uireme stn , etc .

3. E tx er lan requi er m tne s • eR uq irem stne which ar esi f or m f ca t ro s ihw ch are txe re nal to eht sys et m na d sti

d ve elopme tn proce ss .e g. tni e or perab ili ty requireme stn , le ig slat evi re uq ireme stn , te c.



Typ se of requi er me tn 1. sU re requi er ments • tS ate stnem ni natur la al ngua eg plus d gai rams of ht e es vr i ec s ht e s tsy em orp iv d se na d sti

po er ita o lan co sn tra stni . Wr tti en for cu ts omers 2. S tsy em requireme tn s • A rts uct ru ed od c mu e tn se itt ng out d te a eli d d se rc ip it o sn of the s tsy em s re vi ec s.

ttirW e n sa a contr tca betw ee n lc ie tn na d contra tc or

3. So tf ware sp ce ific ita no • A deta li ed so tf ware descrip it on which can es r ev as a ba sis for a de is gn

ro i pm lem atne tion. T eseh set of requir me e stn ra e written for de lev op re s

sU er requirements • hS ould d cse ribe func it onal and non-fu itcn no la requirem stne so taht ht ey a er

under nats dab el by s sy tem u es rs hw o od n’t have deta li ed cet h cin al knowledge • U es r re uq irem stne are de enif d usi gn natur la la gn uag ,e tab sel na d diag ar ms S mo e of ht e p or ble sm with nat ru al language 1. Lack of clarit y

• Precision is dif if cu tl iw thout m ika ng the od c mu tne dif if cu tl to read 2. Requirements co fn u is no

• Fu itcn onal and non-fu itcn onal require stnem net d ot be m exi d-up 3. Requirements ama gl am ita on

• Se ev ar l diff ere tn er quirem stne may be expr esse d toge ht er S etsy m er quireme tn s • More deta li ed specif aci tio sn of user requireme tn s • Ser ev as a b sisa for d ise g in ng eht sys et m • May be u es d as part of eht ys stem co tn r ca t • S tsy em er quirem stne m ya be xe p er ess d u is ng system m do e sl


S fo wt are E ign nee ir ng 10 SI 51 Interfa ec spec cifi a noit Mo ts tsys ems mu ts opera et htiw o ht er s sy tems and eht oper ita ng i tn erfaces mu ts be spe ic f ei d as part of eht re uq irem tne s Thr ee types of tni e fr ca e may vah e to be d fe ine d • rP o dec ru al tni er af ec s • D ta a s rt u tc ru es taht are exchan eg d • D ta a r pe r se e atn tion s

F mro la nota it o sn are na effec it ev t ce h in que for tni erfa ec sp ce if aci ti no

hT e requir me ents docume tn The re uq irem stne od c mu tne si t eh o iff c lai ats teme tn of tahw si er quired of eht ys stem de lev oper .s It hs uo ld ni clude bo ht a de inif tion and a sp ce ifi cation of requirem tne s The er quire stnem docume tn si NOT a desi ng docum tne . As af r as po iss b el , ti shou dl set of AHW T the s tsy em should od ra eht r ht an OH W ti hs ould do ti . Requir me ents docu nem t re iuq er ments – hT e r uqe ire em nt doc hs ould ha ev the of ll o niw g :

• Specify external s sy tem beha iv our • Specify i pm el me tn ation co tsn ra tni s • Easy to c ah nge • Ser ev as er fere cn e tool of r ma netni ance • Record of re ht ou thg ab uo t the efil cycle of ht e

system i e. . rp edict hc anges • Char ca et rise respo sn es to u xen pec et d e tnev s



eR quirem stne od cume tn st ur cture - These ra e the av rious co tn e stn that the req od c hs oul d po ss e ss :

• I tn rodu itc on • lG o ss ar y • U es r re uq irem stne d fe i in ti no • S tsy em arc ih tecture • S tsy em er quirem stne spec ifi cati no • S tsy em mode sl • S tsy em evolu it on • App ne d ci es • Index Requir eme nts engin ee r ni g rp o ec ess s The proc sse es used for RE vary widely depending on eht a pp il ac tion d mo a ni , eht p oe p el

vni o evl d and ht e orga zin ation de lev po gni t eh re uq irem tne s The es are some of eht generic ac it iv t sei co omm n to a ll p or ec ess s • eR uq irem stne e il c ti ation • eR uq irem stne analysis • eR uq irem stne va il d ita on • Re uq irem stne management

eF a ibis lity stu id es A ef asibi il ty ts udy de ic des hw ether or not ht e p or op des s tsy em is wor ht w lih e tI si a sh ro t focu des ts udy t ah t checks

• fI eht s tsy em co tn ribut se to ro ga asin tional ob vitcej es • fI eht s tsy em can be eng eni ered u gnis c rru e tn et chnology and iw t nih budget • fI eht s tsy em can be tni egr ta ed with o ht er s sy tems aht t are u es d

ilE citation and a isylan s • Some mit es c ella d r qe uire nem ts e il c ati tion ro re uq irem stne d csi overy • nI vo vl es t ce h cin al ts a ff wor ik ng iw th customers ot f ni d out about eht app cil ation

od m nia , ht e ser civ es ht at the s tsy em should pro iv de and eht sys met ’s opera it onal co tsn rain st


S fo wt are E ign nee ir ng 10 SI 51 • May vni olve end-users, m na a eg rs, eng ni ee rs vni ol ev d in ma tni enance, doma ni

experts, trade u in o sn , te .c T seh e are ac ll ed ts a ek h lo de sr Requir eme nts va dil ation • Concerned htiw d me o tsn ar it ng that eht requi er men st d fe ine eht system that the

cu ts omer aer lly wants • Requirements error cos st are hi hg so va il da it on si ev ry i pm or tnat

Fi ix ng a requi er me stn e rr or a tf er d le ivery may co ts pu to 100 it mes eht co ts of ixif n g an mi plement ita on error

Requir eme nts man ga e tnem • Requirements nam ageme tn si t eh pro ec ss of managi gn chang gni requir me ents

ud ring the r qe uirements en nig eering proce ss an d ys stem de lev opme tn • Requirements are ni e tiv ably inco pm etel and ni c no tsis ent

eN w re uq irem stne emer eg dur gni t eh proce ss sa bu nis e ss needs hc a gn e na d a b tte er

under nats ding of eht s tsy em si develop de ffiD er tne view op stni ha ev dif ef re tn requireme stn and t eseh are o netf co tn ar dict ro y

Requir eme nts change • T eh pri ro ity of re uq irem stne from d ffi ere tn iv we op ni ts c ah nges rud ing ht e

d leve opment rp ocess • S tsy em cust mo ers may spe ic fy requi er me stn from a ub nis e ss persp vitce e t tah

conf tcil with end-user r qe uirem tne s • T eh business na d cet h cin al envi or nme tn of eht s sy tem changes during sti

d leve opment Dep ra tme tn of CSE, S BJ IT P ga e 21


NU I 4 T SYST ME MOD SLE , RP OJ CE T ANAM G ME E TN

S tsy em mode sl

S etsy m om d le i gn : S tsy em om d gnile helps ht e a an l tsy to under ts and eht fu cn tionality of ht e system na d m do e sl are used to co mm u in ac te htiw cu ts omers Di eff rent mode sl rp e tnes the ys stem f mor d effi rent perspect evi s • Exter lan persp ce evit showing the s tsy em’s co tn e tx or envi or nm ne t • heB a iv or la perspe evitc sho iw ng the b ahe vior of eht s sy tem • rtS u tc u ar l perspec vit e showi gn t eh s etsy m or d ta a arc ih tectu er Str tcu ured metho sd • Stru tc ru ed me oht ds cni o pr or ta e s tsy em dom e il ng as an i ehn re tn p ra t of ht e me ht do • eM ht ods de enif a set of mod sle , a rp oc sse for d re iv gni ht ese mode sl and rules and

guidel ni es t ah t shoul d pa p yl to the mod sle • SAC E ot o sl us pport s etsy m om de gnil sa part of a ts ru tc ru ed me ht od Cont xe t mode sl • Co tn ext mode sl era u des to lli u ts r ta e the uob ndaries fo a tsys em • So laic na d or ag nizational co cn er sn may aff ce t the de ic sion on hw ere to po itis on

system b uo ndar ei s • crA etih ctur la om d sle show eht a s tsy em and its rel ita o sn hi p iw th o ht er s tsy ems

rP oc sse mode sl • rP oc sse mod sle show ht e overa ll pro ssec and eht proce ss es taht are s pu por et d by

eht s sy tem • D ata lf ow m do e sl may be u es d to hs ow eht proce sess and ht e flow of fni orma it on

f mor one pro ec ss ot na o ht re

eB ha iv o ru al mode sl • Behavi uo ral m do e sl are used t o d se cribe eht ov are ll b he a iv our of a s sy tem • Two types of b he a iv oural m do el era hs o nw eh re

• aD ta proce gniss mode sl taht hs ow how d ta a si proc esse d as it mo sev ht rou hg ht e s tsy em • St eta mach eni mod sle ht at show eht s etsy ms respo esn to ve e tn s

• Both of ht e es mode sl are re uq ired for a de cs rip it on of eht s metsy ’s beha iv our Da at -proc nisse g mo sled • D ata lf ow diagrams are u es d t o om del ht e s sy te ’m s data pro ec iss ng • T seh e show eht proce gniss ts eps as d ta a lf o sw ht rou hg a s tsy em • I tn r isni c part of many an la ys si em thods • miS ple na d ni tu ti i ev nota it on t tah cu ts omers can under ts and • hS ow ne d-to- dne proce gniss of da at Object dom e sl • Ob ej ct mode sl d se c ir be eht metsys ni et rms of object alc sses


S fo wt are E ign nee ir ng 10 SI 51 • An ob ej ct c ssal si an ab ts rac it on o ev r a set of bo jec st with common ta tr bi utes na d

eht es rvi ec s po( eratio sn ) pro iv d de by each ob ej ct • Various obje tc m do e sl may be rp odu ec d • ehnI r ti ance m do els • A gg r age tion mod sle • etnI raction mod sle Object dom e sl • N ta ru al wa sy of re lf e tc i gn t eh re la -w ro ld entities am nipula et d by the s sy tem • More ab ts ra tc titne i se era more dif if cu tl ot model u gnis th si approach • Ob ej ct class identification si r ce o esing d as a d fi ficu tl proce ss requiring a deep

under nats ding of eht app cil ation domain • Ob ej ct classes er celf t gni dom nia ent iti es are reu as b el ca or ss s tsy ems

hT e U in fied Mode nil g Langu ga e • D esive d by the d ve elopers of widely u es d bo j ce to tneir ed analys si and de ngis

methods • Has b ce ome an fe fect vi e ts anda dr of r ob ej ctorie tn ed mode ill ng • Nota it on

• Obj ce t lc a sess are rectangles iw th ht e man e ta ht e t po , a tt r bi u set In he midd el ces tio n

na d opera it o sn in t eh bo tt om es c it on • Relations ih ps be wt e ne bo j ce t lc a ss es k( nown as a ss oci ita no s) are hs o nw sa l ni es il n ik ng bo stcej

• ehnI r ti ance is r fe e rr ed ot as gener la isation na d si hs o nw ‘up raw ds’ ra eht r ht an ‘do nw ward ’s ni a eih rarchy Pro ej ct Ma an gemen t

tI si concer en d iw th act ivi ties i vn o evl d ni e sn ur ni g aht t so tf ware si delivered on emit na d on ehcs du el na d ni ca cordan ec with eht requ ri em ne ts of eht ro ag n asi tio sn

d ve eloping na d proc ru gni the so wtf are

rP o ej ct mana eg me tn si neede d b ace use so tf ware developm tne si alwa sy subje tc ot

b du teg na d sc eh dule co tsn ar ni ts that are es t by eht or ag n si ation d ve elop gni eht so tf ware

oS ftwa er ma an g eme nt sid tinct oi ns • T eh produ tc si tni an ig ble • T eh produ tc si u in que yl fle ix ble • So tf aw er e nign eering si not r ce o ing ez d as na en ig n ee ring d si cipl eni iw th t eh as me

ts atus sa mechanic la , ele tc r ci al eng eni ering, te c. • T eh so tf ware developm tne pro ec ss si not ts anda dr si ed • aM ny so awtf re proj ce st are 'one-o ff ' rp ojects Ma an ge em nt act ivi t sei • rP opo las writing includes isaeF b ili ty, P or j ce t co gnits , evO ra ll re uq ireme stn

( etnI rnal and E etx rnal), terms dna cond iti ons • Res uo rce r qe uir me e stn also ni clude P re so nn el sel ce it on Dep ra tme tn of CSE, S BJ IT P ga e 23

S fo wt are E ign nee ir ng 10 SI 51 • rP oject plan in ng and ehcs du il ng • rP oject mo tin oring and r ive e sw a sl o in lc du gni Perso nn el and Proc sse evaluati no • Re rop t wr iti ng and rp e tnes a it no s

rP oj ce t ts aff ni g invo vl es the fo ll owi gn • May not be po iss ble to pa po tni ht e ide la peop el to work on a pro ej ct • rP ojec t b du eg t may not lla ow of r ht e u es of gih hlypaid st ffa • St ffa with t eh a pp or pr ai te xe perie cn e may not be va a li able • An or ag n itazi on may wish to develo p me ployee s sllik on a so tf ware pro tcej

aM na eg rs ha ev to work w nihti ht ese co tsn ra stni esp ce ially when ( sa si cu rr tne ly t eh ca es ) ht ere si an tni er an tional hs ro t ga e of sk elli d IT fats f

rP oj ce t p al n gnin • rP obably the om ts t mi e-co sn um gni proj ce t m na agem tne ca t ivi ty • Co nitn ou us ac it vity f mor initial concept ht rou hg t o s sy te m d le ivery. lP a sn must be

regularly rev esi d sa new fni mro a it on becomes a liav able • Various d fi ferent types of plan may be developed to us ppo tr eht niam so wtf are

proj ce t p nal t ah t si co cn re ned htiw sche ud el na d b du teg Typ se of proj ce t p al n

rP oj ce t p al n structu er – It hs o lu d ni clude ht e fo ll owi gn : • I tn rodu itc on • rP oject or ag n zi ation • iR sk analysis • H ra d raw e and so awtf re re os ur ec re uq irem ne ts • Work br dkae o nw • rP oject sche ud el • Mo tin oring na d repor gnit mecha sin ms A tc ivi ty o gr a zin a it on • A ivitc ties ni a pro ej ct hs ou dl be ro ga in ez d to p or ud ec tangib el ou pt u st of r

m na a eg me tn to j du eg progre ss Dep ra tme tn of CSE, S BJ IT P ga e 24

S fo wt are E ign nee ir ng 10 SI 51 • liM est no es are ht e ne d- op tni of a proc sse act ivi ty • D ile v re ables ra e pro ej ct r se u stl de vil ered t o cu ts om re s at eht ne d of so em m oja r

proj ce t p esah su hc as specific ita on ro de gis n • T eh waterfa ll pro ec ss a ll o sw f ro ht e ts raightfor raw d d ife nition of prog er ss

m li e ts ones

rP oj ce t schedu nil g • Sp til pro ej ct tni o ta sks and e its m eta time and re os ur sec required ot comp tel e each

task • rO gan zi e tas sk conc rru tne ly to m ka e po mit al u es fo wor fk or ec • M ini mize ta ks dep ne dencies to avoid dela sy ac used by o en at sk wait gni for

ano ht re t o comp tel e

• Dep ne d tne on rp o ej ct mana eg rs tni u iti on and Experienc e

hT e proj ce t cs hed gnilu proc se s Sche nilud g pr bo l me s • Es it mating ht e di ff ci ulty of problems na d hen ec the co ts of developing a solu it on

si ha dr • rP oduc ivit ty si not p or por it onal to the numb re of people w ro ik ng on a at s k • Adding pe po el to a tal e proj ce t makes ti tal re be ac use fo commu cin ation

overh ae ds • T eh u xen pec et d alwa sy ah ppe sn . wlA a sy a ll ow contingency ni p al n in gn


S fo wt are E ign nee ir ng 10 SI 51 A tc ivi ty network

Risk manag me ent • iR sk nam ageme tn si co cn er en d iw th id ne tif gniy ris sk and rd a gniw up pla sn to

m imini ez ht eir effe tc on a proj ce t. • A risk si a p or bab ili ty tha t s mo e adverse circumst na ce will oc uc r.

• rP oj ce t ris sk aff ce t sc eh dule or er so ru c se • orP ud ct r sksi affe tc ht e qu ila ty ro per of mr na ce of ht e so wtf are being d ve elop de • Bu nis ess ris sk af cef t the organ zi ation develo ip ng ro proc ru gni eht so wtf are

hT e ris k man ga e em nt rp o ec ss • iR sk id ne tification

• Id itne fy orp ej ct, p or ud ct na d ub enis ss ri ks s • iR sk analysis

• A ssess t eh kil el hi ood and co esn qu ne ec s of the es risk s • iR sk p al n in ng

• Draw up p al ns to avoid or minim si e the ef ef c st of eht r si k • iR sk mo tin ro ing

• Mo tin ro ht e ris sk throu hg out eht pro ej ct Risk di entif ci ta ion • Tec nh ology risks • Pe po le ris sk • rO gan zi ational ri ks s • Requirements risk s • E its mation risks Risk a isylan s • A ss e ss p or bab ili ty and ser oi u ns ess of ea hc risk • rP obab ili ty may be very low, lo ,w moder ta e, ih gh or very h gi h Dep ra tme tn of CSE, S BJ IT P ga e 26

S fo wt are E ign nee ir ng 10 SI 51 • iR sk ef ef c st m thgi be tac a orts p cih , es rious, to el ra elb or ni s gi nifican t Risk lp ann ni g • Consider ae hc risk and de lev op a ts rate yg to manage that risk • Avoid na ec ts rate ig es

• The pr bo ab ili ty t tah eht risk w lli ar si e si reduce d • M ini mization ts r ta egies

• The i pm act of ht e r ksi on the pro cej t or produ tc lliw be re ud ec d • Co itn ngency plans

• fI the risk ar si es, co itn n neg cy pla sn are pla sn ot de la with ht at r si k Dep ra tme tn of CSE, S BJ IT P ga e 27


UNIT –5 OS F WT AR E DESI NG

Sof wt ar e D ise g n Ar ihc et ct laru iseD gn

• E ats b sil h gni eht o ev r lla tS ru utc re of a so tf ware s sy tem . Obj ce vit es • To tni roduce so awtf re ne g eni ering and to expla ni sti i pm ortan ec • To tes out ht e an ws ers t o key qu itse o sn about so awtf re eng ni ee r ni g • To tni roduce e iht cal na d rp o sef sional ssi ues and t o expla ni why ht ey are of concern t o so tf eraw eng ni ee rs

So wtf are ar tihc ce t ru e • The d ise gn proce ss for identif iy ng the sub-s tsy ems ma gnik up a sys et m na d ht e fram we ork for us b-s tsy em cont or l na d commu acin tion si eht arc ih tectu lar d gise n • The output of t sih desi ng proce ss si a d cse rip it on of eht so wtf are arch ti ect ru e

Arch tceti ur la de is gn

• nA ae rly sta eg of ht e system de ngis proc sse • eR pr se ents the li kn be wt e ne spe ic fication and de is gn pro ec ss es • fO t ne ca rr ei d out ni para ll el with so em spec ifi ac tion act seitivi • tI invo vl es id ne tif niy g maj ro s etsy m com op ne stn an d ieht r commu acin tions

Ad tnav ages of xe pl tici cra ih tecture

• tS akeholder co mm u cin ati no : Arc ih tecture may be used sa a focus of d si cu iss on by s etsy m ts akeholders • S tsy em anal isy s: eM sna t ah t analys si of hw et eh r ht e s sy tem ac n m tee sti non fu itcn no al re uq irem stne si op iss ble ro not. • aL gr e- cs a el reu :es T eh arc ih tecture may be reusab el rca o ss a ra egn of s sy tems

Ar ihc cet t ru al De is gn De isic o sn Ar ihc cet t ru al d ise gn pro ssec S etsy m ts ur ctur ni g: T eh s sy tem si d ce o pm osed ni to se ev ral pr ni cip la sub- ys ste sm and co mm u in c ita ons betw nee th se e sub-s tsy e sm are id ne tif ei d.

Co tn or l mod ile n :g A model of eht co tn rol rela it o sn hips bet ew en ht e differ tne par st of ht e s etsy m si e ats bli hs ed.

oM du al r decom op is ti no : The identified sub- sys te sm are decom op es d ni to modules Dep ra tme tn of CSE, S BJ IT P ga e 28


buS - sys tems and mod lu es • A us b- tsys em si a s sy tem ni its o nw rig th who es po era it on si indep ne de tn of ht e es rvi ec s pro iv ded by o eht r sub-s sy tems. • A om dule si a s sy tem com op tnen th ta pro iv des es vr ci es to o eht r com op nents ub t ow ul d not normally be considere d as a separate s sy tem Ar ihc cet t ru al models • ffiD ere tn arch ti ce t ru al mode sl may be p or ud ced duri gn eht desi ng proc sse • aE hc mod le rp e stnes d fi fer tne perspec vit es on eht m ar tihc ecture • tS a it c ts ru tc ur la mod le taht hs ows the major s sy tem c pmo one tn s • Dynamic proc sse model aht t sho sw ht e proc sse ts ru tc ure of eht s etsy m • I tn er af ec om d le ht at de senif sub-s sy tem tni er af ces • eR l ita no ships m do el su hc as a data- lf ow m do el Ar ihc cet t ru al st ly es The arch ti ce tu ar l dom el of a s tsy em may con rof m to a neg eric arch ti ce t ru al mod le o r st ely . An awareness of seht e st ly es can mis p il fy t eh p or blem of de nif i gn s sy tem arc etih ctur se • Howeve ,r most l ra ge sys et ms are he et roge en ous and od not fo ll ow a nis gle

arch ti ce t ru al st ly e Ar ihc cet t eru tta r ubi t se • Perfo mr a :ecn Loca il ez opera it o sn ot minimize sub-s sy tem co mm u in ac tion • Securit :y esU a layered ar ihc t ce t ru e w hti rc itical asse st in in en r la ey r s • Safet :y sI ola et safety-crit ci al com op nen ts • vA a ali bilit :y Include r de und tna com op nen ts ni the a cr tih e tc ure • aM ni t ia nab ili ty: sU e if ne-gra ni , es lf-co tn a ni ed co opm tnen s

syS tem structuring • Co ecn nr ed htiw d ce o pm o gnis the s tsy em ni to etni ra tc i gn s bu -s tsy ems • The arc ih tectur la de ngis si n ro m la ly exp er ess d sa a block d gai ram p er se itn ng an o ev vr iew of ht e s sy tem ts ructure • More spe ic f ci mode sl hs ow gni how sub-s tsy ems share da at , are d tsi ribu et d and etni rfa ec iw th each o eht r may a sl o be d leve oped Pac nik g ro ob t control sys et m

I metsys

tcejbO

cifitnedi a noit metsys

P kca a gnig noitceles

metsys

P gnikca metsys

Dep ra tme tn of CSE, S BJ IT

V noisi

Arm tnoc r rello

reppirG tnoc r rello

oC nvey ro tnoc r rello

P ga e 29

S fo wt are E ign nee ir ng 10 SI 51 S tsy e m O gr na zi a noit

The er po tis ory model

• uS b-s tsy ems mu ts exchange data. T sih may be do en ni wt o wa sy : • hS ared da at si held ni a ec tn ral d ata base or repo tis ro y na d may be a cc e ss ed by a ll sub- s metsy s. • Each sub- tsys em ma tni ai sn sti own da at ba es na d pa ss es d ta a xe p icil tly to o eht r sub- s tsy ems

• hW en l ra ge am uo stn of data are t o be hs era d, eht repo tis ory m do el of hs aring is mo ts commonly used.

loot ESAC s te arch tceti u er

I giseD n edoC otide r eneg ra rot

giseD n Pr tcejo Pro marg lsnart a rot rotisoper y rotide

giseD n R trope resylana eneg ra rot

eR po tis ory model c ah r ca et rist ci s Adva tn ages

• E iff cie tn way to ahs re large ma ou stn of da at • Sub-s etsy ms n ee d no t be co ecn r en d htiw how d ata si produ ec d • Ce tn ra il zed m na a meg e tn e.g. b ca kup, es curity, te c. • ahS ring m do el si bup hsil ed as eht repo tis ro y schema

asiD dva tn a eg s • Sub-s sy tems um ts ag eer on a r pe o tis ory data model. nI e iv tabl y a co rpm o sim e • Da at evolution si d fi f ci u tl and xe pe sn ive • No scope for spe fic ic manageme tn op il c ei s • Di ff ci ul t to d tsi r bi ute iffe ciently

ilC e tn -se revr a cr h ti e tc ure

• siD tribu det s etsy m om d le ihw ch sho sw how d ta a na d proc isse ng is d tsi ributed acro ss a r gna e of co pm onents



• Set of nats d- la o en servers w ih ch pro iv de sp ce if ci se vr ic se su hc as rp itni ng, d ta a m ana gement, te c. • Set of ilc e tn s w hcih call on ht ese es r iv ces • Netw ro k ihw ch lla ows ilc ents to acc sse ser ev rs

a mliF nd p tci u il er b ar r y

neilC t 2 eilC tn 3

W edi - nab d ten htdiw work

utciP re res v re

itigiD z de tohp o rg a shp

ilC e tn -se revr chara tc eri its c s Adva tn ages

• D tsi ribu it on of data si ts rai hg tfor aw dr • aM sek ef ef ct vi e use of netw ro ked s etsy ms. May require cheaper ah rd aw re • Ea ys to add wen servers or upgrade sixe t gni servers

asiD dva tn a eg s • No ahs er d data om d le os sub-s sy tems use d fi f re ent d ta a orga in zation. D ta a tni erchange may be ni e ff icien t • eR dund na t anam geme tn ni each server • No c tne ral reg tsi er of man es and es r iv c se - ti may be h ra d ot f ni d out hw at servers na d es vr ci es are ava li ab el

Abst ar ct mac nih e m do le

• sU ed to m do el eht etni rfac gni of us b- tsys ems • Orga in zes eht s sy tem tni o a set of la ey rs ro( ab ts ract mach ni es) each of ihw ch p or iv de a tes of es r iv ces • uS pp ro st eht ni creme tn al developm tne of sub-S sy te sm in d effi rent layers. hW en a la ey r i tn erface hc anges, only t eh adj ca ent lay re si affected • However, fo net di ff icu tl ot struct ru e s etsy ms ni th si way


I 1 tneilC eilC tn 4

trepyH e tx res v re

trepyH e tx web

Ca lat o ug e V oedi res v re res v re

Ca lat o eug mliF pilc selif


oisreV n ma emegan nt ys s met

V tnemeganam noisre

tcejbO tnemeganam

esabataD metsys

repO a gnit metsys

C no rt ol lytS e s Co tn or l mod le s: Are co ecn r en d iw ht eht co tn rol flow be wt e ne us b-s tsy ems.

siD t ni ct from eht sys et m d ce om op itis on model • Ce tn ra il ze d co tn or :l enO sub-s tsy em has over lla re ps onsib ili ty f ro co tn rol na d ts ar st and ts po s o ht er s bu -s sy tems • Event-ba es d co rtn o :l aE hc sub-s tsy em ac n er spo dn to e tx ernally ge en r eta d ve e stn from o ht er us b- tsys ems or ht e s sy tem’s envi or mn ent

Ce tn r ila zed co tn rol

• A co rtn ol s bu -s sy tem takes r se po isn b ili ty for ma an ging the execu it on of o ht er sub-s sy tems • llaC -r te urn mod :le Top-do nw s bu r uo nit e mod le hw ere co tn rol ts ra st at eht ot p of a su rb uo t eni h ei rarchy and om sev dow awn rds. pA p il cable to es uq e itn al s tsy ems

• M na ager mod :le App cil able to co cn urre tn sys smet . One s tsy em co pm onent co tn ro sl the ts opp gni , ts ar it ng and c oo rd ni ation of o ht er sys et m proce ss es. naC be i pm leme tn ed ni es qu itne al s sy tems sa a c sa e ts a met ent

C lla - ter urn mo ed l

niaM

pro marg

R 2 enituo R 3 enituo

R 1.3 enituo R 2.3 enituo


I

I

R 1 enituo

R 1.1 enituo R 2.1 enituo


Real- it me etsys m c no rt o l

I osneS r utcA a rot

pr sesseco pr sesseco

metsyS tnoc r rello

noitatupmoC resU F tlua pr sesseco cafretni e reldnah

E ev nt-d evir n sy ts ems: Dr nevi by externally generated ve e stn where ht e it im ng of the

eve tn si uo tw ti the co tn or l of ht e sub-s tsy ems ihw ch proce ss eht ve e .tn

T ow pr ni cipal eve tn - rd vi en om dels • Broadc tsa om d sle . An eve tn si broadc tsa t o a ll s bu -s tsy ems. Any sub-s tsy em ihw ch can handle eht eve tn may do os . • I tn e rr upt-dr vi en mode sl . Used ni real-time s tsy ems hw er e

etni purr ts are detec et d by an tni errupt hand el r and p ssa ed ot some other co pm one tn for rp oce niss g

htO er eve tn dr vi en m do e sl ni clude s rp ead hs ee st and produ itc on sys et ms

Bro da c tsa mod le • E eff ct vi e ni ni tegrat gni s bu -s tsy ems on dif ef rent co pm u et rs ni a

wten ork • uS b-s tsy ems reg si ter an tni ere st ni spe ic f ci eve stn . When t eh s e occ ru , cont or l si trans ef rr ed to eht s bu -s etsy m wh hci can hand el eht ve ent

• Co tn rol po il cy si not emb de ded ni eht eve tn and ssem ag e handle .r Sub-s tsy ems de ic de on ve e stn of tni ere ts to eht m • However, us b-s sy tems don’t nk ow fi ro nehw an eve tn w lli be handle d

vitceleS e bro acda s it n g

I

tnevE dna assem eg reldnah


buS - etsys m buS - metsys 3 4

buS - etsys m buS - metsys 1 2

S fo wt are E ign nee ir ng 10 SI 51 In et r ur pt-d ir v ne sy ets m s

• sU ed ni real- it me s sy tems where tsaf r se po sn e t o an eve tn is sse ential • There are kno nw i etn rr upt typ se with a hand el r de nif ed for ae hc type • Each type si associa et d iw th a memory loca it on and a hardware swit hc

cau ses tr na sfer to sti hand el r • Allows fa ts res op sn e but c mo plex to program na d d fi ficu tl to va il d ta e

In et r ur pt-d ir v ne oc rtn o l

I

tpurretnI v rotce

eldnaH r reldnaH 1 2

Pr sseco Pr sseco 1 2

Mod lu ar ed c mo po tis oi n ytS les

• nA oth re ts ructur la level where sub-s etsy ms are decom op sed tni o modules

• T ow om du al r deco pm o is tion mod sle covered • An bo ej ct mod le where eht s tsy em si deco pm o es d tni o

etni r ca ting ob ej cts • A data- lf ow mod le where eht s tsy em si deco pm o es d tni o fu cn tional modu sel which t ar nsform ni up st to ou pt u st . A sl o nk own as ht e pipe nil e mod le • fI po iss bl ,e de isic o sn about co cn urr ne cy hs oul b d e d le a ey d u litn modules are mi plemented

Obje tc model s

• rtS ucture ht e s etsy m tni o a tes of ol ose yl c uo ple d objects iw th ew ll-de if ned tni e fr ac se

• Object- ro iented d ce mo op is tion si co cn erned with ide itn fyi gn object alc s ses , th ie r attributes na d opera it o sn • hW en mi pleme tn ed, ob ej c st are c aer ted f mor ht ese c al sses na d some co tn rol model u es d to oc ord ni a et ob tcej opera it on s


stpurretnI

eldnaH r reldnaH 3 4

Pr sseco Pr sseco 3 4

S fo wt are E ign nee ir n g

Invoice proc gnisse sy ets m I

remotsuC

#remotsuc eman

da dr sse tiderc doirep

Pa tnemy

inv #ecio da et

tnuoma #remotsuc

taD a-flo w mo ed sl

• Func it onal tra fsn orma it o sn proce ss ht eir inpu st to p or du ec out up st • M ya be r fe er er d to as a pipe and lif ter model (as in INU X she ll ) • aV riants of t sih appro ca h are ev ry c mo om n. hW en transforma it o sn era es qu laitne , th si si a bat hc qes u ne tial model

ihw ch si e tx e sn ively u es d ni da at proce gniss s tsy ems • Not aer lly su ati b el for ni tera tc i ev sys et ms

Doma ni -specif ci a tihcr e tc ure s • Arch ti e tc ural mod sle which are sp ce if ci t o some a pp il cation dom ia n • T ow typ se of dom nia -specific dom el • G ne er ci m do e sl which are ab ts r itca o sn from a n bmu er of real sys et ms and ihw ch encapsulate ht e pr icni pal chara tc re si tics fo ht e es sys et ms • feR re ence m do e sl which are more ab ts ra tc , idea il zed m do el.

rP o iv de a em a sn of inf ro m ita on ba uo t ht at class of system and of comparing d fi fer tne arc ih tectur se • Ge en ric om de sl are usually bo tt om-up m do e ;sl eR fer ne ce mod sle are top-do nw om d le s

Obje tc -o ir e etn d De is g n

• Desig in ng sys smet u gnis self- co atn ined bo ej c st and ob ej ct cla ss es

Chara tc e scitsir fo OO D

• Objects are ab ts ra itc o sn of real-w ro ld or s etsy m entities and m na age t eh msel ev s • Objects are ni depend ne t na d ne capsulate tats e na d repre tnes ation fni mro a it on . • S tsy em fun itc no a il ty si expr sse ed ni te mr s fo ob tcej es rvice s


15SI01

R tpiece

inv #ecio da et

tnuoma #remotsuc

inv #ecio da et

tnuoma remotsuc

eussi )( rednimeRdnes )( tnemyaPtpecca )(

tpieceRdnes )(

Inv ecio


• hS ared da at ar ae s are e il m ani ted. Ob stcej commu in cate by m sse a eg pass ni g • Objects may be d si tribu et d dna may e ex cu et es uq ne tially o r ni para ll el.

Interactin g bo ej c st

I Adva tn ages of O DO • E isa er ma ni tenance. Objects may be under ts ood as ts and- la one e itn tie s • Objects are app or rp tai e reu as ble co pm one stn . • oF r some s tsy e sm , ht ere may be an ob iv ous m pa ping from real w ro l d ne tities to s tsy em objects

Obje tc -o ir e etn d dev ole p em n t • Object- ro nei ted anal sy is, de ngis and progra mm ni g are r le ated but d nitsi ct • OOA si co cn erned iw th developing an ob tcej mo led of ht e a pp il c ita on dom ia n • OOD si co cn erned iw th developing an ob tcej -orie etn d s sy tem model t o mi pleme tn requirements • OOP si co cn er en d w hti aer li iz ng an O DO u is ng an OO program gnim langu ga e such sa Ja av or +C + Obje stc and o jb tce essalc s • Ob ej c st are ne t ti i se ni a software s tsy em w hcih repre tnes tsni anc se of aer l-

wor dl and s sy tem entities • Ob ej ct classes are templa set for obj ce st . They may be used to crea et bo tcej s • Ob ej ct classes may inherit attributes na d es r iv c se rf om o eht r object lc a ss es Obje stc • An Ob ej ct si na entity w hcih has a tats e na d a de enif d es t of op are it o sn

w ih ch oper eta on ht at ts at .e T eh ts ate si repr tnese ed as a set fo ob tcej a tt ri ub tes. The oper ita o sn ssa o taic ed iw th ht e obj ce t pro iv de ser iv ces ot other bo je stc ( ilc e stn ) wh hci request seht e es rvices when some co pm uta it on si required.

• Ob ej c st are cr ae ted a cc ording ot some ob tcej cla ss de if n iti on. An obje tc

cla ss de inif tion serves as a te pm tal e for bo j ce st . tI ni cludes d ce al ar it o sn of



a ll the a tt rib setu and es r iv c se which shou dl be a ss oc ai ted iw th an obje tc of ht at c al ss.

The Unified M do ile gn La ugn ag e

• Several differe tn nota it o sn f ro de cs ribing bo ej ct-o ir e tn ed de is g sn rew e propo es d ni ht e 1980s dna 1990s • The nU ified Modeli gn La gn ua eg si an tni egration of eseht nota it ons • tI describes no itat o sn for a number fo differen t mode sl ht at may be p or ud c de d ru gni OO na alys si and d ise gn • tI si now a de af cto nats da dr of r OO m do e il ng

Emplo eey ob ej ct lc a ss (UML)

I

Obje tc oc mm inu ca it o n

• Co cn eptually, obj ce st commu in ac te by me ss age p sa sing . • M sse a eg s • The an me of ht e ser iv ec er qu etse d by eht ca ill ng ob .tcej • oC pies of the inf ro m ita on er quired to ex ce u et the s re iv ce na d

eht man e of a hold re of r ht e r se u tl of eht es vr ice. • In prac cit ,e me ss ages era o tf en implem tne ed by pro ec du er c lla s • Name = pro dec ure name . • fnI or itam on = parameter tsil .

Me ss a eg axe mple s

// Ca ll a htem od a ss o taic ed htiw a bu eff r // ob ej ct that r te ru sn eht next value

// ni t eh buffe r v = ci cr ularBu ff er.Get (); // Ca ll ht e method ssa ociated htiw a // thermo ts at bo j ce t aht t stes ht e



// t me perature to be ma tni a eni d eht omr ts at.setTemp (20);

Gen ilare z ita on na d ni h atire nce

• Objects are members of c al sses w ih ch d ife ne attribute types and opera it o sn • lC asses may be ra ranged ni a cla ss h ei rarchy w eh re one lc a ss (a us per-cla ss ) si a ge en ra zil ation of one or more hto er salc ses (sub-

cla ss es) • A s bu - lc a ss inher sti t eh attributes na d opera it o sn rf om sti super cla ss and may add wen m ohte ds or tta r bi ut se of its o nw • Ge en ra il az tion ni eht UML si mi pleme etn d sa hni er ti an ec ni

OO rp ogram im ng la gn uages

eg A n ilare z oita n h crarei h y I

Adv tna a seg fo in tireh a cn e

• tI si an ab ts rac it on mecha sin m which may be use d to clas is fy ne tit ei s

• tI si a reuse mechan msi at bo ht ht e d ise gn na d eht progra mm gni leve l • The inher ti a cn e graph si a so ru ce fo or inag az tional nk o elw dge about doma sni na d s tsy ems

Prob el ms htiw in tireh a cn e

• Object alc sses are not fles -co tn a eni d. ht ey ca nn ot be und re ts ood w hti out re ef ren ec to ieht r us per- lc a ss es • Desig en rs have a tendency to reu es ht e inh re ita cn e graph cr tae ed dur gni analys si . naC lead to is gnif ci a tn inefficiency • The inher ti a cn e grap sh of an la sy is, d ise gn and i pm el me tn ation ha ev dif ef re tn functio sn na d hs ould be es parat yle m tnia a eni d



In tireh a cn e a dn OO D

• Th ere are d effi r gni v ei ws sa t o whe eht r hni er nati ce si fundam tne al to DOO . • iV ew 1. Id tne if iy ng the inh re ti ance eih rarchy ro ne wt ork is a fundam tne al part of ob ej ct-orie tn ed de ngis . Ob iv ou yls th si c na only be mi p mel ented u is ng na O LPO . • weiV 2. ehnI r ti an ec si a u fes ul i pm el me tn ation con ec pt ihw ch a ll o sw reuse of tta ribu et and operation d ife nitio sn . Id ne tifying a n inher ti ance hie ar rchy at eht desi ng ts age p al ec s nu nec se s ra y restr ci tio sn on eht implem tne a it no • I ehn ritance tni roduces comp el xity and siht si unde is ar bl ,e espe ic ally ni critical sys et ms

MU L ssa o ic a it o sn

• Objects na d ob ej ct clas ses par it cip ta e ni r ale tions ih ps htiw other bo j ce st and obje tc alc s es s • In ht e UML, a ge en ra il zed rela it ons ih p si ind ci a et d by an a ss o aic ti no • ssA o ic atio sn may be a nn otated htiw i fn orma it on ht at d se crib se

eht association ssA ociatio sn era ge en ral ub t may i dn i ac et ht at na a tt ri ub te of an bo ej ct si an a ss o aic ted objec t or that a method r ile es on an ssa ociated ob ej ct

nA association dom el

I

oC ords c1, c2 ; S ta el il te sat ,1 sat2 ; Na giv ator th Ne a iv gator ; pu ilb c Po is tion g vi ePosition () {

return cur er ntPo is tion ; }


S fo wt are E ign nee ir ng 10 SI 51 C no rruc e tn obje stc

• The an t ru e of ob ej c st as se fl -co tn a ni ed ent iti es m ka e them suitable for co cn ur er tn i pm el me atn tion • The m sse a eg -pa gniss mod le of ob tcej co mm u in ac tion can be i pm leme tn ed dir ce tly fi obj ce st are running on separ ta e rp o ssec ro s ni a d tsi ribu et d s sy tem

vreS e sr and a vitc e obje stc

• S re vers: The bo j ce t si mi pleme etn d as a para ll el orp c sse ( es rve )r with tne ry po stni co rr espond gni to ob tcej ope ar it o sn . n fI o c la ls are made to ti , ht e ob ej ct suspends sti e fl and iaw ts for f ru eht r requ stse for s re iv ce • Ac vit e ob :stcej Objects are imp el me etn d sa par lella pro sessec and eht i etn rnal ob ej ct ts ate may be hc a egn d by the obje tc ti se fl and not is pm ly by e etx r lan ca sll .

Obje tc - O ir e tn e d de is gn pro sec s Acti ev rt a sn ponde o r bje tc

• Ac vit e ob stcej may have ht eir tta ributes om d ifi ed by ope ar it o sn but may a sl o u dp a et eht m autono om u yls u is ng tni ernal po era it o sn • Tr sna pond re ob ej ct rb oadca sts an ia rcr tfa ’s po itis on. T eh po itis on may be u dp a et d u is ng a sate till e op is tion gni s sy tem. The object periodically u dp ate eht po itis on by tr ai ngula it on fro m as t tille es.

nA a itc ve rt anspon ed o r bje tc

cla ss T ar n ps onder e netx ds Thr ae d { Po itis on c rru Ptne o itis on ;

p bu cil void run () {

elihw (t ur e) {

c1 = as t .1 op is tion )( ; c2 = as t .2 op is tion )( ; curre tn Po itis on = theNav gi ato .r co pm ute (c1, c2) ; } }

} T// ran ops nder Ja t av h aer d s

• Threads ni Java ra e a mis p el co tsn ruct of r i pm el m ne ting co cn u rr tne ob ej cts • Threads mu ts ni clude a m hte od llac ed run() and siht si started up by the Java run- it me s sy tem



• Ac vit e ob stcej typi ac lly ni clude na i fn tini e l oo p so ht at they are alwa sy ac rr gniy out the pmoc uta it on

nA ob ej ct-o tneir ed ed ngis pro ssec

• Def eni ht e co tn e tx and mod se of use of ht e s etsy m • Design ht e s sy tem arch ceti ture • Identify the rp ni cip la s tsy em ob ej c st • De lev op de ngis om d sle • Sp ce ify ob ej ct tni er af ec s

Layer de arc tih e rutc e

I

syS tem co tn xe t a dn mod sle of u es veD elo p an underst na ding of t eh relations ih ps be wt e ne the so wtf are

being de engis d an d sti e etx rnal envi or nm ne t • S tsy em co tn ext: A st cita model ht at describ se o eht r s sy tems ni

eht en iv ronme tn . esU a subs sy tem mod le to hs ow o ht er s tsy ems. Fo ll owi gn ils de hs o sw the s tsy e sm arou dn the we ehta r ats tion sys et m. • oM del of metsys use: A d any mic om d le ht at de cs rib se how ht e sys et m etni racts with its environme tn . esU u es - ac ses to hs ow

etni r ca tions



buS syste ht ni sm e htaew e m r a ipp n g sys met

I

U es -case s of t r he w ae th re ts a oit n I

esU - ac s ed e s irc p noit S etsy m eW ather st ita on

esU - ac se eR port cA tors eW ather data co ll ce tion s etsy m,

eW ather st ita on taD a T eh ew ather ts a it on sends a

summary of t eh ew at reh data taht has been co ll e etc d f or m ht e

tsni ru stnem ni ht e col cel tion per oi d to eht weather data co ll ection sys tem. The data tnes are eht max mi um inim um m and

eva ra eg g or und na d ia r et pm eratu er ,s the maxi mum , im ni um m and a ev ra eg air

rp e ss ru es, eht ma ix mum, im ni um m an d a ev ra eg niw d



speeds, eht to lat ar infa ll and eht wind dire itc on sa sampled ta 5

nim ute s tni erva sl . mitS ulus The w ae ther da at co ell ction

ys stem e ats b sil hes a m do em il nk iw th the ew ather ats tion and

re uq e sts tra sn m si sion of ht e da at . Respo sn e The summar zi ed data si se tn to

ht e ew ather d ta a co ell ction ys stem

Comme tn s eW ather st ita ons are usually as ek d to r pe or t o ecn per hour but

siht frequency may differ fro m o en ts a it on to ht e o eht r and may be om d ifi ed in fu ut re

crA h eti ctu lar de gis n • nO ce i tn eractio sn be wt e ne t eh s tsy em and sti en iv ro tnemn ha ev b ee n under ots od, yo u u es siht fni or itam on for de gis n gni eht system arch ti ect ru e • La ey red ra tihc e tc ru e si app or priate for ht e w ae ther ts a it no • nI terf ca e la ey r f ro hand gnil c mo mu in cati no s • D ta a co itcell on layer for ma an g gni tsni ur m tne s • I tsn ruments layer f ro co ll ce t gni d ta a • Th ere should be on more naht 7 itne ties ni an ar hc i et ctur la mod le

We hta er st ita on cra h eti ctu er

I Obje tc id itne fic ita o n

• Identif iy ng ob ej c st (or ob cej t c sal ses) si t eh mo ts d fi ficu tl part of obje tc oriented d ise gn • Th ere si no 'ma cig formu al ' for ob ej ct id ne tification. tI re seil on

eht sk lli , xe p re ie cn e and od m nia know el dge of system de is gners • Objec t identification si an ti erat vi e pro ssec . You era u kiln le y to

teg ti right fir ts time Dep ra tme tn of CSE, S BJ IT P ga e 43


Appro ca h se to id itne fic ita o n

• sU e a gra mm at ci al approa hc b esa d on a an t ru al la gn ua eg descrip it on of ht e s sy tem (used ni H oo d me ht od) • saB e t eh identif aci tion on tangib el iht n sg ni the app il cation dom ia n • sU e a be ah vior la ap rp oach and id ne tify obje stc based on what par it cipat se ni wh ta be ah vi ro • sU e a s ec an rio-ba des a an lys si . T eh obj ce st , a tt rib tu es na d m hte ods in each cs enario ra e id ne tifie d

We hta er st ita o n ob tcej c ssal e s

• G or u dn ht re mom et re , nA emom te er, raB ometer: App acil tion dom nia ob ej c st th ta are ‘ ah rd aw re’ bo stcej r le ated to ht e tsni rum stne ni eht sys et m. • eW ather st ita no : T eh ba is c ni terface of eht ew ather st ita on to sti envi or mn e tn . tI eht ref ro e re celf ts ht e tni re actio sn ide tn i eif d ni the u es -c sa e mod le • eW ather data: E cn apsulates ht e summar zi ed data from the

sni trum tne s We hta er st ita o n ob tcej c ssal e s

I

Fu tr h tcejbo re s ejbo dna c r t e if ne tnem • sU e dom nia knowled eg to ide itn fy om re ob ej c st and po re ations • eW ather st ita no s hs ould ha ev a u in que identifi re • eW ather st ita no s are remote yl s ti u ta ed so tsni rument fail ru es ha ev to be reported autom cita ally. Ther fe ore attr bi utes na d oper ita o sn for se fl -chec ik ng are requir de • Ac vit e ro p ssa ive object :s In t sih ca es , objects are p evissa and co ll ce t d ta a on reque ts ra eht r ht an auto mon ously. T sih tni ro ud ec s fle ix b ili ty at the expen es of co rtn o ll re proc isse ng t mi e



eD s gi n om d le s • Design mode sl hs ow eht ob ej c st na d bo je tc cla ss es and re al tions ih ps be wt e ne ht ese entitie s • tS a it c mod sle de cs ribe ht e ts a it c ts ruct ru e of eht s etsy m ni ter sm of ob ej ct c al sses and r le a it ons ih p s • nyD amic mode sl d se cribe ht e d any mic tni re actions b ewte en ob cej ts.

maxE p el s ed fo s gi n om de sl • uS b-s tsy em om de sl that show lo ig cal gro pu in sg of bo je stc tni o co eh rent sub tsys ems • Seque cn e mode sl taht hs ow ht e sequ ecne of bo je tc tni re actions • tS ate am c nih e mod sle that show how ni di iv du la o cejb ts hc ange ht eir ats te in respo esn t o events • Other mod sle ni clude use-c sa e mod sle , gga re ag tion mod sle , ge en ra il az tion om d sle , e ct .

uS b ys s om met dels • hS ows how eht desi ng si orga in ez d tni o lo ig cally re al ted rg oups of obje tc s • In ht e UML, ht ese are hs o nw u is ng p kca ages – an encapsula it on co tsn ruct. T sih si a lo ig cal m do el. hT e tca ual

ro ga in az tion of ob cej ts ni the s sy tem may be d fi ef re tn . IWe ta h re s oitat n bus s metsy s

qeS uen om ec d le s • Seque cn e mode sl hs ow eht sequence of bo ej ct tni er itca o sn t tah take place • Ob ej c st are ra ra gn ed h ro zi o tn ally acro ss ht e top • Time si repr etnese d ev r it ac lly so om d sle are read top to bottom • nI ter ca tio sn are repr se ented by lab le ed arro sw , effiD re tn st ly es of arrow re rp e tnes d ffi ere tn types of etni rac it on



• A niht er c nat gle ni an bo j ce t fil e nil e rep er se stn the t mi e when eht ob ej ct si ht e co tn ro ill ng bo ej ct ni the s etsy m

taD a noitcelloc s qe uen ec

I

tS atech stra • hS ow how bo j ce st r se pond ot d fi f re tne ser civ e requ stse na d the ts a et

tr na sitio sn tri egg red by seht e requ stse • fI ob tcej ats te si hS ut od wn ht en ti r se ponds to a tS ra tup )( me ss a eg In

ht e waiting ts ate ht e objec t si wa iti ng for fur eht r me ss a eg s • fI report eW a ht er )( neht s etsy m om sev to summ ra zi i gn ts a et • fI c ila rb a et () eht ys stem moves to a ca il br gnita ts ate • A co ll ce t gni tats e si tne ered when a clock s gi nal si r ce vie ed



We ta h tats re ion s etat dia marg

I

ejbO c tni t e afr c e s noitacificep • Objec t ni ter af c se have to be specified os taht eht ob stcej and other co pm onents can be d ise g en d ni p ara ll el • Desig en rs should va oid d gise n gni the etni r af ce repr se ent ita on but hs ou dl ih de siht ni the bo j ce t ti self • Objects may have several etni r af ces w ih ch are viewpo stni on

eht meth do s pro iv ded • The U LM u ses class diagr sma f ro ni t re af ec specification but J ava m ya a sl o be u des

We ta h ats re oit n inte afr c e etni rfa ec Weather tS a it on {

p bu cil void eW a ht erS at tion )( ; p bu cil void startup () ; p bu cil void startup ( tsnI rume tn i) ; p bu cil void hs utdo nw )( ; p bu cil void hs utdo nw (In ts ur m tne i) ; p bu cil void reportW ehtae r ( ) ; p bu cil void tset () ; p bu cil void tset ( tsnI rum tne i ) ; p bu cil void ca il brate ( tsnI ru tnem i) ; p bu cil ni t get DI )( ; } W// ae eht r tS a it on



eD s gi n ulove t noi • iH ding fni orma it on ni side obje stc means aht t cha gn es made to an ob ej ct

do not ffa ect o ht er objects ni an un rp ed ci tab el way • ssA ume po ll u it on mo tin ro ing af c ili t sei are to be added ot w ae eht r

ats ti no s. T seh e sample t eh air na d compute eht am uo tn of d effi re tn po ll ut stna ni eht ta mosphere

• Po ll u it on read sgni are tr sna m tti ed with w ae ther data

hC a segn re uq ired • A dd na bo j ce t cla ss ca ll ed A‘ ir qu ila ty’ sa part of

eW atherS itat no • A dd na po re ita on r pe or iAt Qr ua il ty t o Weather tS a it on. idoM f y ht e co tn or l so tf ware to co ll ce t po ll u it on aer ding s • A dd ob ej c st er pre nes it gn po ll u it on om tin or gni sni trume stn

lloP u oit n om n iroti n g

I

• DOO si an appro ca h to desi ng so that d ise gn components have their o nw rp vi ate ats te and po are it o sn

• Obj ce st should vah e co tsn ructor and sni pec it on op are it o sn . They p or iv d e es rvic se to o ht er bo ej cts



• Obj ce st may be mi plemented sequ itne ally or concurren lt y • The Unif ei d Mod gnile La gn ua eg orp iv d se d ffi ere nt nota it o sn for

de if n gni d effi re tn object om d le s • A range of d fi fer tne om d sle may be p or du ec d during na bo j ce t- ro ie tn ed

de ngis pro ssec . These ni clude ts a it c and d any m ci system mod sle • Obj ce t tni er af ces hs ould be d fe ined rp e sic ely u is ng e.g. a programming

la gn uage like J va a. • Obje tc - ro tnei ed d ngise si pm il f sei s etsy m evolu it no



NU IT –6 veD e mpol e tn

R pa id Sof wt ra e D ve elopmen t

eB ac use of rapid yl chan ig ng bu ssenis en riv onments, bu enis sses have to r se pond to wen op op tr u in ties and compe itit on. T sih requir se so tf wa er and rap di developm tne and d vile ery si not o tf en the om ts rc ti ical re uq irem tne for so tf ware s sy tems. Bu enis sses may be lliw i gn to ca cept low re qu ila ty so wtf are fi rapid delivery of e ss ential functiona il ty si op iss ble.

emeriuqeR n st

eB ac use of the changing en iv ronme tn , ti si o tf en mi po iss b el to a rr vi e at a stabl ,e co tsisn e tn set of s etsy m er quirem ne ts. Theref ro e a aw et rfa ll model of d ve elopm tne si mi pra itc c la and an appro hca to developme tn ba es d on itera evit spe ic f ci a it on an d d evile ry si t eh only way to de vil er so wtf are qu ci kly.

hC a ar c ret i its cs of RAD pr co sse e s • The proce ss es of sp ce ification, de is gn and mi ple nem tation are

concurr .tne There si no d te a eli d sp ce ification and d ngise doc mu e itatn on si m imini zed.

• The s etsy m si develop de ni a es r sei of incr me ents. End u es rs evaluate each cni rement and ma ek p or posa sl for later cni rem stne .

• S etsy m u es r etni rfaces are usually d ve eloped u nis g an tni eract vi e develo mp e tn ys stem .

nA i et itar ve de lev opme tn pr co sse

I

Adv tna a seg fo in erc m tne a l ed lev opme tn

• cA celerated de il v re y of cu ts om re se vr i sec . caE h cni rement de il vers ht e ih g tseh prio ir ty fu cn tiona il ty to the cu ts omer.



• sU er engagement tiw h the sy ts em. esU rs ha ev to eb i vn olved ni the develo mp e tn which me sna the s tsy em si mo er il kely to me te ht eir re uq ireme stn and eht u es rs are more comm ti ted to eht s sy tem.

Prob el ms htiw in erc m tne al ed lev opme tn

• tnemeganaM :smelborp ssergorP nac eb drah ot egduj dna smelborp drah ot dnif esuaceb ereht si on noitatnemucod ot etartsnomed tahw sah neeb enod .

• lautcartnoC :smelborp ehT lamron tcartnoc yam edulcni a ;noitacificeps tuohtiw a ,noitacificeps tnereffid smrof fo tcartnoc evah ot eb desu .

• noitadilaV :smelborp tuohtiW a ,noitacificeps tahw si eht metsys gnieb detset iaga n ?ts

• ecnanetniaM :smelborp launitnoC egnahc sdnet ot tpurroc erawtfos erutcurts gnikam ti erom visnepxe e ot egnahc dna evlove ot teem wen stnemeriuqer .

rP oto yt pin g oF r some al rge s tsy ems, cni reme tn al eti rat vi e d ve elopme tn and de vil ery may

be mi p car it ac l; th si si se peci la ly true when mu itl ple aet ms are wor gnik on d ffi ere tn s seti .

rP ototyping , where an exper mi e tn al system si d leve oped as a ba sis for formula it ng eht requi er me stn may be u es d. T sih s sy tem si thro nw awa y when ht e s sy tem spe ic fication sah been agreed.

Incremental deve ol mp en t and proto yt pin g

I C no lf i nitc g obje vitc e s The ob ej c evit of ni crem tne al d ve elop tnem si to d le iver a w ro gnik s sy tem to ne d-u es rs. The d leve op nem t ats r st w hti tho es requirem stne which era be ts

under ots od. The ob ej c evit of ht or w-away prototyping si to va il date ro d re vi e ht e sys et m requirem stne . The prototyp gni proc sse ts ra st iw th those er quire stnem w ih ch are po ro yl under ots od.

gA ile me oht d s • iD s as t afsi ction w hti t eh o ev rheads vni o vl ed ni desi ng m hte ods led ot the

cr ae it on of a elig htem ods. T seh e meth do :s • Focus on eht c do e ar eht r than ht e d ise gn; • Are ba es d on an ti era it ev appro ca h to s fo awt re d ve elop ;tnem



• Are tni ended ot d vile re wor ik ng so tf ware qu kci ly and ve o vl e th si quickly ot m ee t changing requirem stne .

• eligA methods era rp obab yl b tse su eti d to ms a /ll medium- is zed bu nis e ss systems ro PC rp oduc st .

P lpicnir es fo iga le meth do sI

r P i i c n l p e D n oi t p i r c s e

C s u t o m r e i n v m e v l o n e t e h T m o t s u c r e h s u o ld e b y l e s o l c d e v l o v n i t u o h g u o r h t e h t d e v e l o p m e n t s s e c o r p . r i e h T e l o r s i e d i v o r p d n a r p e s i ti r o i w e n s y s t e m m e ri u q e r s t n e d n a o t e t a u l a v e e h t s n o i t a r e t i f o e h t m e t s y s .

t n e m e r c n I i l e d l a y r e v e h T w t f o s e r a s i d e p o l e v e d n i m e r c n i s t n e w i th e h t s u c m o t r e g n i y f i c e p s e h t m e r i u q e r s t n e o t e b i d e d u l c n n i h c a e m e r c n i . t n e

e l p o e P o n t s s e c o r p e h T s l l i k s f o e h t m p o l e v e d t n e t m a e d l u o h s b e o c e r n g i d e s d n a e l p x o i t d e . T e h m a e t d l u o h s e b f e l t o t o l e v e d p r i e h t w o n w s y a f o w o r k i n g w i t h o u t p r e s c r e v i t p i . s e s s e c o r p

E m e c a r b h c e g n a E t c e p x e h t s y s t m e m e r i u q e r s t n e o t n a h c e g d n a n g i s e d t e h m e t s y s o s t t a h t i n a c c c a m o m e t a d o h t e s e h c n a . s e g

t n i a M l p m i s n i a y t i c i s u c o F n o m i s i c i l p ty n i o b th e h t w t f o s e r a e b g n i d e p o l e v e d d n a n i t h e d m p o l e v e t n e p o r s s e c d e s u . W r e v e r e h s s o p ib l , e t c a i y l e v w k r o to l e im e t a n i m o c p l i x e ty m o r f t e h m e t s y s .

Prob el ms htiw a lig e m te hod s

• tI ac n be d fi f ci u tl to ek ep ht e i etn rest of cu ts mo e sr hw o are invo evl d ni eht proc sse .

• eT am members may be u sn u eti d to eht tni ense invo evl me tn ht at ahc racteri ez s a lig e methods.

• Prior iti zing changes can be d fi ficu tl hw ere the er era mu itl ple ts akeholders.

• aM ni t ia ning simp il city requir se extra work. • Co tn ra stc may be a pr bo el m as w hti oth re approa hc es to ti er vita e

develo mp e tn . Ex rt em e pro rg amm ni g

• Perhaps ht e b tse -kno nw and om ts iw de yl used a lig e m hte do . • Extreme rP ogram im ng (XP) kat es an e‘ tx reme’ pa pro ca h to iter ita ve

develo mp e tn . • eN w ev r is no s may be ub tli ves are l it mes per day; • I cn reme stn are d vile ere d to cu ts mo ers e ev ry 2 w skee ; • llA te sts um ts be run for ve ery bu li d na d ht e bu li d si only ca ec p et d fi

set ts ur n suc fssec u ll y. Dep ra tme tn of CSE, S BJ IT P ga e 52


The XP ler e esa c lcy e

I

emertxE p or g immar n g p ar c ecit s 1

Increm en tal p al nn ing R equirem en ts are record ed no Sto yr C ards and th e tS ories to be incl du ed in a re lease are determ ined by the tim e availab el and their rela it ve prior ity. The deve lope rs break these S tor ies into dev e lop m ent Ō as ksÕ

m S a ll R el ae ses T he minim al u se uf l set o f func it ona lit y tha t prov ides ub siness va lue is deve loped first. R eleases of the system are rf equen t and increm en tally add func ti no a l ti y to the first relea se.

S i m ple D esign E on gu h d e sign is carried o u t to m eet the c u rre n t require m e n ts a dn on m ro e.

T es t first dev e lop m ent An auto m ated un it tes t fram ew o rk is u sed to wr ite tes ts for a new p iece of func ti no a il ty be fore tha t function ality itse lf is i m ple m ented .

R efactoring A ll develope rs ar e expec ted to refacto r the c do e con it nu uo s ly as soon as po ssib le code im prove m en ts are fou dn . This keeps the code sim p el and m ain tainable.


T .


emertxE p or g immar n g p ar c ecit s 2

e gnikcehc ,sriap ni krow srepoleveD a Õrehto hc d syawla ot troppus eht gnidivorp o .boj doog a

p ehT a ved fo sri e fo saera lla no krow srepol taht os ,metsys eht ved esitrepxe fo sdnalsi on e dna pol nwo srepoleved eht lla a eht ll

co .ed hc nac enoynA na g .gnihtyna e

w sa noos sA o o kr n eht otni detargetni si ti etelpmoc si ksat a hw o metsys el . na retfA y eht ni stset tinu eht lla ,noitargetni hcus

.ssap tsum metsys

revo fo stnuoma egraL - on era emit t oc n elbatpecca deredis a eht s ten e ff e si tc o tf e r ot n edu ec code qua til y m dna e muid mret

ivitcudorp ty

ne eht fo evitatneserper A d- resu o )remotsuC eht( metsys eht f ohs u eb dl va a rof emit lluf elbali ht e maet PX eht fo esu . I n an

orp emertxe g gnimmar p cor e uc eht ,ss s eht fo rebmem a si remot si dna maet tnempoleved opser n nignirb rof elbis g metsys

t eht ot stnemeriuqer e .noitatnemelpmi rof ma

XP and ag eli irp cn ip sel

• I cn reme tn al de lev o mp e tn si s pu ported ht rou hg sm lla , frequ tne sys et m r ele ases.

• Cu ts o em r vni o evl me tn mea sn fu ll - it me cu ts omer gne ageme tn with ht e aet m.

• People not pro ec ss ht uor hg pair programm gni , co ell c vit e ow en rship na d a rp oce ss aht t avoids lo gn w kro ing hours.

• hC a gn e suppor et d orht u hg regular system r ele ases. • aM ni t ia ning simp il city throu hg co tsn ant refactori gn of c do e.

qeR u emeri nts soiranecs

• In XP, u es r re uq irem stne are xe p er ess d sa cs enarios or u es r ts ro sei . • These are wr tti en on rac ds na d ht e de lev o mp e tn et am brea sk ht em do nw

tni o mi ple nem tation tasks. The es tas sk a er eht ba sis of hcs e ud el na d co ts mitse ates.

• The cust mo er ohc o ses the ts or sei for ni clu is on in ht e ne tx er le sa e ba es d on ieht r rp ior iti es an d eht cs hedule itse ma .set


mmargorP riaP i gn

evitcelloC O pihsrenw

C ounitno u etnI s g itar on

aniatsuS b el ap ce

nO - etis remotsuC

s work and


otS r c y ard fo r d co u em n t d wo n aol ding XP and c ah n eg

• Co vn entio lan w si dom ni so tf ware en nig eering si ot de ngis for cha egn . tI si w ro th sp ne ding time and e ff ort itna cipa gnit changes sa siht redu sec

co sts tal re ni eht l fi e cyc el . • PX , howe ev r, ma tni ai sn that th si si not wor wht h li e as cha segn ca nn ot be

rel ai bl y anticipated. • aR t eh r, it rp opo ses co tsn ant code mi pro ev me tn r( afe ctorin )g to make

hc ang se eas ei r when they have to be mi plemented

eT s it n i g n PX • eT st- if r ts developme tn . cnI rem tne al te ts de lev po nem t from sc ane rios . • sU er i vn o vl eme tn ni tset developm tne and av lida it on . • Automa et d tset harness se are used to run a ll compo tnen te sts each it me

taht a n we re el ase si bu tli . eT s sac t e de cs r oitpi n


S fo wt are E ign nee ir ng 10 SI 51 Test-fir ts dev ole pmen t

• Wr gniti tests b fe ore code lc arifies t eh re uq irem ne ts to be mi p mel ented. • eT sts are wr ti t ne as programs rath re ht an d ta a so taht ht ey can be

xe ecu det aut mo a lacit ly. The te ts ni clud se a c eh ck ht at ti sah executed co tcerr ly.

• llA pr ive ous and en w stset are automa cit ally ur n hw en n we functiona il ty si added. Thus ehc ck gni t ah t eht new fu cn tio ilan ty has not tni rodu ec d

errors. Pa ri p immargor gn In XP, programmers work ni p ia rs , tis ting to eg t eh r to de lev po c do e. T sih help s d ve elop c mo mon owner ihs p of c do e an d s rp eads nk o elw d eg ac or ss ht e team. tI es rves sa an inf mro la review proc sse as each nil e of oc de si l oo ek d at by

more naht 1 person. tI e cn uo r ga es r fe a tc or gni as the hw o el team c na benef ti f mor siht . aeM s ru eme stn su gg e ts ht at developme tn produ ivitc ty with p ria programming si sim ali r ot that of wt o p oe ple w ro ik ng ni dep ne d ne tly. R pa id pa p il c ita on dev le op em n t Ag li e methods ha ev re ec ived a lot of tta ention but o eht r a pp roac seh to rap di a pp cil ation d ve elopm tne ah ve been u es d for many years. The es are d ise g en d to d ve elop da at - tni e visn e bu nis e ss app il catio sn and r yle on programming and pr se ent gni inf mro a it on from a databa es .

AR D e rivn no ment too sl • Da at b sa e rp ogram im ng la gn uage • I tn re f eca gener ta or • niL ks to o ciff e app il cation s • eR port gen are tors

A RAD en oriv n em n t

I


S fo wt are E ign nee ir ng 10 SI 51 In ret face genera it o n

• aM ny app il cati no s are b sa ed ra uo dn complex for sm and developing ht ese fo mr s m na ually si a t emi -c no sum gni act ivi ty.

• DAR en iv or mn ents ni clude us pp ro t for sc er en gen are it on ni clud ni g: • I tn eractive form de inif tion u gnis dr ga an d rd po t ce h in que ;s • F ro m iknil ng w eh re the es quen ec of of rms to be prese etn d si spec ifi ed; • F ro m v re ification w eh re lla o ew d r gna es ni f ro m fi le ds are de nif ed.

V lausi pro arg mm gni

• Script gni la gn u ga es su hc as siV ual Basic us pport siv ual p or gra mm gni hw ere the prototype si d leve oped by creat gni a u es r etni fr a ec f mor

ts andard ti ems na d ssa oc itai ng compo nen ts with the es items • A al r eg il rb ary of co pm one stn e stsix to support t sih type of d ve elopme tn • These may be t lia ored to su ti ht e spe ic fic app il cation re uq irem stne .

V lausi pro arg mm gni htiw re su e

I

melborP s tiw h iv s oleved lau p em n t

Diff ci u tl to c oo rd tani e et am-b sa ed developm tne . No exp il c ti sys et m arc etih cture. Comp xel dep ne de icn es betw ee n par st of ht e program ac n cause ma tni ainability pr bo lems.

r STOC e esu • nA effect vi e approach to rap di de lev opm tne si to conf gi ru e and il nk

ex itsi ng o ff the she fl sys et ms. For e ax pm el , a requirem stne managem tne system could be bu tli by u is n :g

• A da at b sa e to ts ore r qe uir me e stn ; • A row d rp oc sse or ot cap ut re r qe uirements and f ro mat rep ro t ;s • A sp er ad hs ee t for tr ca eability mana eg me tn ;



moC pound docu em n st oF r some a pp cil atio sn , a prototype c na be cre eta d by developing a compound

docume tn . T sih si a doc mu e tn iw th ac vit e e el ments (su hc as a sp er ad hs ee t) ht at a ll ow user co pm uta it o sn . Each ac vit e ele me tn has na assoc etai d

a pp cil ation which is vni oked hw en th ta ele me tn si sele tc ed. T eh docume tn sti elf si eht tni egr ta or for eht d effi re tn app cil atio sn .

App oitacil n il n ik n g

I S fo wt are proto yt p gni • A rp ototype si an initial version of a s etsy m u es d to de om tsn rate con ec p st and try out de ngis op it o sn . A rp ototype ac n b e used :ni • The requireme stn engineeri gn proce ss t o help w ti h r qe uire nem ts

ile citation na d va il dation; • In d ise gn proce sess to expl ro e op it o sn na d develop a UI de ngis ; • In ht e test gni proc sse to run ba kc -to-b kca te sts . Be en f sti o f proto yt pin g

• mI pro ev d s etsy m u as b ili ty. • A closer m ta ch to users’ re la en eds. • mI pro ev d d ngise qu ila ty. • mI pro ev d ma ni ta ani b ili ty. • eR duc de developm tne e ff ro t.


S fo wt are E ign nee ir ng 10 SI 51 Ba kc to ba kc test ni g The prototyp gni proce ss

Throw-away proto yt p se

• rP ototypes sh uo dl be d si ac rded tfa re de lev opm tne as ht ey are not a good ba sis for a produ itc on s tsy em:

• tI may be impo iss ble to tu en eht ys stem to m tee non-functional re uq ireme stn ;

• rP ototypes era normally undocume tn ed; • The prototype rts u tc ure si usually degraded ht rou hg rapid c gnah e; • The prototype p or bab yl w lli not m ee t on mr la ro inag az tional qua il ty

ts andards. tfoS w ra e noitulove tfoS w ra e hc a egn • So tf eraw change si ni ev ti ab el • eN w requir me ents emer eg when t eh so awtf re si u es d; • The ub enis ss environme tn changes; • Er or rs mu ts be er pair ;de • eN w co pm ut re s na d e uq ipm tne si added to ht e s sy tem; • The perf ro ma cn e or re il ab ili ty of the system may ha ev to be im rp oved . • A key pr bo lem for ro ag nisati no s si imp el menting na d manag gni

ahc nge to ht eir e six ting so wtf are ys stems Dep ra tme tn of CSE, S BJ IT P ga e 59

S fo wt are E ign nee ir ng 10 SI 51 I pm o tr na c e of evolu it o n Orga zin atio sn ha ev huge inve ts me stn ni ieht r so wtf are s sy te sm - they a er crit ci al bu nis e ss essa ts. To m tnia a ni ht e value of ht ese asse st to eht business, ht ey mu ts be c ah nged na d u dp a det . The maj ro ity of eht so wtf are bud teg ni al rge compa in es si devo et d to evo vl i gn e itsix ng so wtf are r hta er ht an

d ve eloping n we software.

pS ri al mod le of ve olu noit P or g ar m evolu oit d n any mic s

rP ogr ma evolution d ny am sci si the ts du y of ht e proce ss es of sys et m cha gn e. fA ter m ja ro e pm ir ci al ts ud sei , Le mh an and Belady propo es d aht t ht ere were a

number of ‘la sw ’ w ih ch app eil d to all s tsy ems sa they evo evl d. T eh re are se isn b el ob es r av tio sn rat eh r than al ws. They are app il ac ble to al r eg s sy tems d ve eloped by large ro ga sin atio sn . Perhaps le ss app acil ble ni o eht r c sa es.


S fo wt are E ign nee ir ng 10 SI 51 Leh am n l s’ a sw i( mpo tr na )t L a w e D rcs ip ti n o

o C nt i n u in g ch na e g A p ro gra m th a t is u sed in a r e a l- w o rld e n v iro m n ne t n e c se sa rily m u s t c h an g e o r b e oc m e p ro g ress iv e l y le ss u s e uf l in ht at

e n vir o n m e .t n

In c re sa i gn c o m p l e xi ty A s a n ev o l v i gn p or g ram ch na g es , i ts s rt uc t u re te n ds to b e c o e m m o er co p m le x . x E tra re sources u m st b e de v o ted to p rese rvin g

a n d s i m p lify ing t eh s tru c t u r . e

L a rge p rog r am v e o lutio n P r o g ar m e v t ul o ion is a s elf - er g u la tin g p r o c sse . S ys tem att ir b utes su ch a s s zi e , ti m e b e t w een r e le a ses a n d the n m u be r f o r ep o r t de er r o r s is pa p r o x i a m tely in v ra ia n t for e ca h s y s te m rele s a e.

gr O an is a tio n al s ta b il ti y O ve r a p ro g ra Õ m l fi e ti m e, i ts ra t e o f d e v elo p m e t n is a p pro x i m at e ly c o nstan t a n d in de p e n d en t o f t eh r ose u rce s

e d v t o ed ot sy s tem d e v el po e m nt.

o C n e s r av tion o f O ve r t eh li tef i m e o f a sy s te m , the in c re m en t a l c h a n g e in f i m a l ai ir ty rele s a e i s a p p r o xi m at e ly c o n s ta n t.

o C nt i n u in g gr o w th T eh fun c ti no a li ty o f f er e d b y s ys te m s h sa to co n tin u ally in c r ae e s to m ia nta in u s e r s a ti s fa c t i o n .

D eclin in g q a u lity T eh q u al ity o f sy s te m s w i ll a pp ear to b e d ec lining u n le ss t h ey are a da p ted to c h a n g e s in t h ei r po er a tio n a l e n v ir no m en t.

e F e d ba c k sy s tem E ov l u ti no p r o ce s ses in c o rp o ra te l u m ti- a g e n t, m u l ti-l o op fee d b a c k ys t s e s m a n d oy u h va e to tr e a t th em as ef e d b ac k sy ts e m s to a c hieve s i g n if i c an t pr o d u ct i m pro v e m ne t.

App cil ba ytili of Leh am n s’ laws Lehm na ’s la sw es em to be ge en rally app il cable to larg ,e t lia ro ed s tsy e sm d ve eloped by large ro ga sin atio sn .

• Confir em d ni more r ce e tn w ro k by Lehman on ht e F AE TS pro ej ct (see f ru eht r read gni on book web is te) .

• tI si not elc ar how ht ey shoul d be om dified for • hS ri kn -w ar pped so awtf re p or du ;stc • S tsy ems taht ni cor rop ate a is g in fica tn numb re of OC TS compo nen t ;s • Sm lla ro ag nisa it ons; • eM dium zis ed tsys e sm .

Sof wt are mainten cna e

oM dif gniy a program a etf r ti sah be ne put tni o use. aM ni tenance od es not nor lam ly invo vl e maj ro c ah nges to eht ys stem’s arc ih tectur .e hC a segn ar e mi pleme etn d by modif niy g e six it gn components and a dd ing en w c mo ponents ot t eh sys et m


s

e a c h

S fo wt are E ign nee ir ng 10 SI 51 Mainte an nce si inev ati b el • T eh s tsy em re uq irem ne ts are il kely to cha gn e w lih e the s tsy em si b ie ng

d leve oped becau es ht e ne vironm tne is chan gnig . T eh refore a de evil red system wo t'n me te sti re uq irem tne s!

• S tsy ems era it gh lt y c uo p el d htiw t ieh r en iv or mn ent. nehW a s tsy em si tsni al el d ni na en iv ronme tn ti cha segn that en iv ronme tn and th re e rof e

changes eht s sy tem er quire stnem . • S tsy ems MUST be tniam ained ht ere f ro e fi they are to rema ni useful ni na

environme tn .

yT ep s of maintena ecn • aM tni enan ec to rep ia r so tf ware af u stl

O Chan ig ng a s sy tem to cor cer t d icife enc sei ni ht e w ya mee st its requir me ents.

• aM tni enan ec to adapt so awtf re to a diff ere tn oper gnita e ivn ronment O Chan ig ng a s sy tem so aht t ti operates ni a d ffi erent en iv ronme tn

(co pm u et r, SO , e ct .) from its ini tial imp el m tne ation . • aM tni enan ec to a dd ot or om dify t eh system’s func it ona il ty

O M do if iy ng t eh system to sitas fy new requi er m stne .

D irtsi bu it o n of main net an ec ffe o tr Mainte an nc e oc sts

• sU ua ll y greater than developm tne co sts (2* to 10 *0 depending on eht app acil tion).

• fA cef ted by ob th techni ac l and non-techni ac l tcaf ors. • I cn reases sa so awtf re si ma tni ained. aM ni t ne ance co urr p st eht so awtf re

st ur cture so ma sek ruf eht r ma tni enance more difficu tl . • gA e gni so tf ware can ah ve ih gh support cos st ( .e g. o dl langua seg ,

comp li ers etc. .)


S fo wt are E ign nee ir ng 10 SI 51 De lev po me m/tn a netni a cn e soc ts

I

Ma netni a cn e soc t factor s

• Te ats ma b ili t y • ecnanetniaM stsoc era decuder fi eht emas sffats era devlovni htiw meht rof

s mo e mit e. • C no rt a utc a er l s nop sib li it y • T ed eh v le o srep o s a f y ets m am y c on evah o pser lautcartn o tilibisn y rof m anetnia cn e

os ereht si on evitnecni ot egnahc erutuf rof ngised .

• fatS f lliks s • ecnanetniaM sffats era netfo decneirepxeni dna evah detimil niamod

lwonk e gd e. • rgorP a m a eg a dn rts u rutc e • sA smargorp ,ega rieht erutcurts si dedarged dna yeht emoceb redrah ot

gnahc dna dnatsrednu e. Ma netni a cn e pr de ict oi n

aM tni ena cn e predic it on si con ec rned htiw ssa essing ihw ch par st of ht e s sy te m may cause p or ble sm and ah ve ih gh ma tni enan ec co sts

hC a egn a cc eptance depends on the mai tn a ani b ili ty of eht com op nen ts affe tc ed by eht chan eg ; mI plement gni chang se degrades ht e s tsy em and er du ec s sti mai tn a ani b ili ty;

aM tni ena cn e co sts depend on the nu bm er of hc ang se na d co sts of change depend on ma ni ta ani b ili ty.


S fo wt are E ign nee ir ng 10 SI 51 Ma netni a cn e pr de ict oi n

I Change p ider ct oi n

• Predic it ng the numb re of hc a gn es er quires and u dn re ts and gni of eht r ale tionships be ewt en a tsys em and sti envi nor me tn .

• T hgi lt y c uo pled etsys ms requi er chan seg whene ev r the envi or mn e tn si hc anged . • Fa tc ors ni flue icn ng t sih relationship are • Number and comp el xity of s sy tem tni er af ec s; • Number of ni h re ne tly vola lit e s tsy em requirement ;s • The bu enis ss proc sse es where eht s tsy em si used.

Complexit m y e rt ic s

• Predic it o sn of mai tn a ani b ili ty ac n be am d e by assessing eht comp el xity of s sy tem compo nen ts . • tS udies ha ev hs o nw t tah mo ts m tnia ena cn e e ff ro t si spe tn on a re al t vi ely ms a ll numb re of s tsy em compo stnen . • Comp el xity dep ne ds on • Comp el xity of co rtn ol ts ru tc ure ;s • Comp el xity of data struc ut er ;s • Object, m hte od (proc de ur )e na d modu el zis e.

orP c sse cirtem s

rP oc sse em a us er ments may be su ed to a ss e ss ma tni a ni a lib ity • Number of reque sts for oc rr ect vi e mai tn ena cn e; • vA are eg time requi er d of r mi pact ana lys ;si • vA are eg time kat en to i pm el me tn a change er qu se t; • Number of ou tst and gni hc a gn e re uq e sts . fI any or all of seht e si ni creas gni , siht may ind ci ate a d ce l eni ni

m tnia a ni ab ili ty. Evolu oit n p cor e ss es

Evolu it on pro ec sess dep ne d on •The type of so wtf are be gni mai tn a eni d;



•The developm tne pro ec sess u es d; •The s lik ls na d xe perie cn e of ht e pe po el vni o vl ed .

rP opo slas rof hc an eg are ht e dr vi er for s sy tem ve olu it on. ahC nge id ne tifi ac tion na d ve olution co nitn ue ht rou hg out eht sys tem il fe it me.

hC an eg itnedi fic ita o n a dn evo ul t oi n

I

The sys love met u oit n p cor ess

I

hC an eg lpmi e nem t ita no

I Ur eg n hc t an eg re uq e ts s Urge tn changes may have to be i pm el me tn ed iw th uo t go gni throu hg a ll ts a seg of the so tf ware engin ee ri gn proc se s Dep ra tme tn of CSE, S BJ IT P ga e 65


• fI a serious s tsy e m fault has to be rep ia red; • fI changes to eht metsys ’s environme tn ( .e g. an OS pu grade) have u xen pected e eff c st ; • fI there are bu is ne ss changes aht t re uq ire a very rap di er ps o sn e (e.g.

eht r le ea es of a compe it ng produ )tc .

emE r eg cn er y ap ir I

yS ste m re-en ig nee ir n g • eR - ts ru tc uring or re-wr iti ng part or lla of a legacy s sy tem

iw thout chang gni its f nu ctionality. • A pp cil ab el where some but not all sub-s etsy ms of a large r sys et m er quire frequ ne t niam et nan ec . • eR - ne g ni eering involv se adding fe fort to m eka ht em e eisa r to m tnia a ni . T eh s tsy em may be re-stru tc ru ed na d re-documented.

Adva tn ga es of er e gn ine re ing Reduc de r ksi •There si a ih gh risk ni en w so wtf are d ve elopm .tne There may be de lev o mp e tn rp bo lems, ts af gnif prob el ms and sp ifice cation prob el ms. Reduc de co ts •The co ts of re- nigne eering si oft ne sig in fica tn ly el ss ht an the co sts of developing new s fo t aw re.

F ro w dra and re-en nig ee rin g

I


Sof wt are E ign nee ir ng 10 SI 51 Th er e -en enig e ir ng orp c sse

I Reen ig n ee ring ecorp s a s c it v iti se

oS u cr e code tra lsn ation •Convert c do e to a wen languag .e

Re ev rse eng ni ree ni g •Analyze the program to under ts and ;ti

rP og ar m ts ruc ut re impro ev ment •Re ts ur ct ru e automa it cally for under ts andab ili ty;

rP og ar m om du al r itazi on •Re ro inag ze eht program ts ruc ut r ;e

taD a reengin ee ring • lC ean- pu a dn re rts u tc ure s tsy em data.

Reen ig n ee ring co tcaf ts ors

I Re-en nig eerin g ap aorp c eh s

• The qu ila ty of eht so tf ware to be r nee g eni ered. • The tool us pport ava ali b el for reengin ree gni . • The exte tn of eht da at co revn sion ihw ch si re uq ired. • The ava li ab ili ty of xe p re t ts a ff for re gne ineeri .gn • T sih can be a rp ob el m iw th o dl s tsy ems b sa ed on cet hnology

taht si no lo egn r iw dely u es d. Dep ra tme tn of CSE, S BJ IT P ga e 67

S fo wt are E ign nee ir ng 10 SI 51 Le ag c y s metsy e noitulov

Orga sin atio sn ht at er ly on legacy s sy tems mu ts ch oo se a ts r ta e yg f ro ve o ivl ng ht e es s tsy ems

•Scrap ht e s sy tem comp etel ly and om dify business proce sess so aht t ti si no longer re uq ired ;

•Co tn inue m iatnia ning t eh s sy tem; •Tra fsn orm eht s etsy m by re-e ign neering to impro ev sti m tnia a ni ab ili ty; • eR p al ec ht e s etsy m iw th a new s etsy m. T eh str ta egy chosen shou dl depend on eht sys et m qu ila ty and sti bu nis e ss value .

yS ste m qua il ty na d b su in se v s alu e

I

Le ag c y s tsy e c m a iroget e s

Lo q w u ila ty, lo w business value •These sys et ms should be cs rapp .de Low- uq a il ty, ih gh-bu nis e ss value •These make an mi porta tn bu enis ss co tn ribu it on but are xe pe sn ive to ma tni a ni . hS ou dl be re- nigne eered or repla ec d if a suitable sys et m si ava li ab el .

hgiH -qua il ty, low-bu nis ess value • eR p al ec iw th OC TS, s arc p comp etel ly or m tnia a ni .

hgiH -qua il ty, h hgi bu nis e ss value •Co tn inue in po are it on u gnis n mro la s tsy em ma tni enanc .e

Bus ni e ss valu a e s msses ent

tnemssessA dluohs ekat tnereffid stniopweiv otni tnuocca •S metsy dne - ;sresu • ssenisuB ;sremotsuc • eniL ;sreganam • TI sreganam ; • roineS sreganam .



weivretnI tnereffid sredlohekats dna etalloc stluser .

yS ste m qua il ty sa se ss ment

Bu nis e ss proce ss ssa essment •How we ll do se the bu nis e ss p or c sse support eht cu rr e tn go sla of eht bu nis ess? En iv ronme tn asse ss ment •How ffe e evitc si the s sy tem’s envi or nme tn and how exp ne s vi e si ti to ma tni a ?ni

pA p il cation asses ms ent • hW at si the qu ila ty of the app il cation software s sy tem?

Bu is n se s p or ces s sa es ssment sU e a v wei po tni -or etnei d a pp roach na d se ke a wsn ers from tsys em

stakeholders • sI there a de nif ed pro ssec om d le na d si ti fo ll o ew d? •Do d fi ferent par st of eht organ asi tion use differe tn proc sse es f ro ht e as me function?

•How sah t eh proc sse b ee n adap et d? • hW at are ht e re al tions ih ps iw th other ub enis ss proce ss es an d a er ht ese nece ss ary?

• sI the proce ss e ff ect vi le y sup rop et d by the legacy app il ac tion so wtf are?

E ax pm el - a tr leva ord re gni s sy tem may have a low bu nis e ss value b ce au es of the iw des rp ead use of ew b-ba es d dro er gni .

En riv no em n ssa t ess em n t 1

tcaF or Ques oit ns

dnU e natsr dab ili ty oH w d ciffi u si tl i t t o dnu e natsr d t eh uos rc oc e de o f t eh curren t s sy tem? woH c mo ple x are t eh contr s lo tr cu tures ht a t a er su ed ? Do variables vah e m ae ni gn ful nam se ht at fer l ce ht t eir f nu ct ?noi

coD u em nta it on hW at system d co umenta it o n is va ailable? sI eht cod umenta oit n com lp e et , oc ns si tent an d up- ot -date?

Da at sI ht e er xe na p ticil da at om led rof t eh ys s ?met To hw at exten t is da ud at p cil ated ni d fi fer f tne i ?sel sI ht e d ta a us de

yb ht e tsys e u m p-to-da et an oc d nsisten ?t

freP o ecnamr sI t p eh e namrofr c e o f the pa plica oit n uqeda a et ? oD ep rfo namr c e pro lb e sm vah e a sign acifi nt e ff ect on sy ts em su e ?sr

tsyS em me rusa ement

Y uo may collect qua atitn it ve d ta a to ma ek an a ss essme tn of eht qu ila ty of ht e app cil ation s sy tem Dep ra tme tn of CSE, S BJ IT P ga e 69


•The number of sys tem hc ange requests; •The number of d ffi ere tn user etni rfac se u es d by the s sy tem; •The vol mu e fo data u es d by eht system.

alB ck-box et s gnit

• Input da at dna ou pt ut er sults o tf en fall tni o diff re e tn lc as ses

hw ere all members of a c ssal are rela et d. • Each of eseht c al sses si an equ vi ale cn e par itit on or od m nia

hw ere t eh prog ar m behaves ni an equ vi a tnel way for each cla ss me bm er. • T tse ca ses hs ould be hc o nes from e ca h part iti on .

E viuq a el n ec pa ninoititr g

I

E viuq a el n ec pa snoititr

I



NU I T 7 V IFIRE CATION DNA VALIDAT OI N

ireV f ci a noit .sv va oitadil n

Verifi ac tio :n "Are we bu li d gni t eh produ tc r thgi ,” The so tf ware hs ould co fn orm ot sti sp ce ific ita on. Va il d ita no : A" re we bu li di gn eht ri thg rp odu ”tc ., hT e so wtf are should do w tah ht e user aer lly re uq ir se .

Th V e orp V & ces s

• sI a whole il fe-cycle pro ssec - V & V must be pa p il ed at e ca h st ega ni eht so tf ware pro ec ss .

• Has two rp ni cipal object vi es • T eh d si covery of defects ni a s metsy ; • T eh sa se ss me tn of ehw ther or not eht sys tem si u fes ul na d useab el

ni an po are it onal s ti uati no

V &V laog s Verifi ac tion and valida it on should tse ab il sh confid ne ce t tah the so tf ware si f ti for p ru op es . T sih od es ON T mean completely free of d efe c st . Ra ht ,re ti um ts be good en uo hg f ro sti tni ended use and eht type fo u es lliw d te e mr eni t eh d ge ree of confidence that si needed.

& V V oc n if d ne ec Depends on ys stem’s pur op es , u res xe p ce at tio sn na d mar tek i gn en iv or mn ent

So awtf re func it on •The level of confide cn e dep ne ds on how cr iti ac l ht e so tf ware si to an orga asin tion .

esU r exp ce at tions • sU ers may have low expecta it o sn of cert nia k ni ds of so tf ware . Marke it ng en iv or mn ent •Ge itt ng a p or du tc to market early may be mo er impor tnat ht an f ni ding de stcef ni ht e rp ogram.

atS t ci a dn dy iman c ev rif ci a it no

• So tf ware sni pec it o sn . Concerned w hti an la sy is of ht e ts atic s sy t me rep er se atn tion to d csi over problems ( ts a it c ev rifi ac it on)

• M ya be supple tnem by tool-ba es d docum tne and code na alysis • So tf ware set t gni . Con ec rned with exer ic sing na d

obser iv ng product behaviour (d any m ci ev rif aci tion) • The s tsy em si ex ce u et d htiw tset data na d sti po er ita onal be ah viour si

observed Dep ra tme tn of CSE, S BJ IT P ga e 71


atS t ci a dn yd iman c &V V

I

rgorP a t m esting Can rev ae l t eh prese cn e of err ro s TON ht eir abse cn .e T eh o yln va il d ita o n et ch in que for non-fu itcn onal er uq irem stne as eht so awtf re has to be xe ecuted ot s ee how ti behaves. Should be used ni co jn u cn tion htiw ts atic ev r ifi c ita on to

pro iv de fu ll V&V coverage.

pyT e set fo s tin g • Defe tc set it ng: eT s st de is gned to d si co ev r system de cef ts. A

su cc essful d fe ce t te ts si o en which re ev a sl t eh rp e nes ec of d fe ce st ni a s sy tem. Covered ni Chap et r 23

• Va il d ita on set t ni g: I tn ended to hs ow taht ht e so tf ware m stee sti requir me e stn . A succe fss ul te ts si one that sho sw taht a re uq irem tne

sah be ne p or per yl imp el me tn ed. Te its n a g dn bed u igg gn

De ef ct set ting and d be ugg gni are d si t ni ct pro ec ss es. V re ification an d va il dation si concerned with tse ab il hs gni the ex tsi en ec of defects ni a prog ar m. eD ub igg ng si con ec r en d with lo ac it ng and repairing t eh se e rr ors. eD bu gg i gn invo vl es f ro mu al t gni a hypo ht es si about prog ar m beha iv o ru ht en set t gni ht ese hypotheses to nif d t eh sys et m err ro .

Th d e ebu igg n p g r co ess

I



& V V p al nn in g aC reful plan in ng si required to get ht e om ts out of test gni and inspe itc on

proc sesse . Plann gni sh uo ld ts art rae yl ni ht e d ve elopme tn proc sse . The p nal hs ould id itne fy the b la ance be ewt en ats t ci verif aci tion and te gnits . T tse

planning si about d inife ng ts andards for eht tset ing pro ssec r hta er than d cse ribing p or duct te sts . Th V e -mode fo l devel po em nt

I The ts ur ct ru e o f a software t se t pla n

• The set ting pro ec ss . • eR qui er m stne tra ec ab ili ty. • T tse ed ti e sm . • T tse i gn sche ud el . • T tse rec ro ding procedur se . • aH rd aw re na d so tf eraw re uq ireme stn . • Co sn tr nia ts .


S fo wt are E ign nee ir ng 10 SI 51 The so wtf are test p al n

The et sting process A csed ir ption of the maj ro pha ses of the testing p or ces .s Th se e might be as descr ebi d e ra lier in th si ahc pt re .

R qe uiremen st traceability Users are om st interes et d in t eh sys tem em e it ng its er q iu rem tne s and t se ting should be planned so that all r qe ui er ments are i dn ivi aud lly test de .

Tested item s The products of the software pr sseco that are to eb test de s oh uld be specified.

Testing schedule An evo rall te ts ing sche ud le and r se ource allocation for this schedule. Th si , obviously, is linked ot the more g ene ral project de ev l po m ne t s ehc dul .e

Test er cording procedures It is not enough simply to r nu test .s T eh resu tl s of the et s ts um st be

sys t ame tically recorded. It must be possible to ua dit the t se ting p or c se s to check ht at it eb en carried uo t corr tce ly.

Hardware na d software requirem ents Th si section sh uo ld set out softw ra e t oo ls r qe uired and esti am ted hardware utilisa noit .

Constraints Co sn traints fa f ce t ni g t eh testing process us hc sa staff hs ortages should be ant ci ipated in this se tc ion.

rawtfoS e insp ce ti no s

The es vni o vl e pe po le exam ini ng eht sour ec repr se e atn tion wi ht t eh ia m of d csi o ev ri gn anoma il es and defe stc . I sn p ce it o sn not er uq ire e ex cu it on of a tsys em so may be used b fe ro e mi pleme atn tion.

They may be app il ed ot any repr nese ta it on of t eh syste r( m qe uirements , d ngise , co gifn u ar it on data, test d ata , etc.). They have been hs o nw to be an ffe ce it ve tech in que for d csi overing progra m errors. In ps e itc on us ccess

Many d fi fer tne d fe ce st may be d si co ev red ni a is n elg sni p itce on. In te gnits , one d fe ce t, may mask ano ht er so several ex ce u it o sn are er quired. T eh reuse dom nia and progra mm gni kno elw dge so

re eiv wers are kil ely to ha ev s ee n eht typ se of err ro ht at commonly ar esi .

Inspect oi ns and t se it n g I sn pec it o sn na d t itse ng a er comp el mentary and not op op is ng ev rific ita on techniques. Both hs ou dl be used dur gni the V & V

proc sse . snI p ce it ons c na check co fn ormance iw th a spe ic fication but not co fn ro m na ec iw th eht cust mo e ’r s er al requireme stn . Inspe itc o sn



cannot hc eck non-functional char tca er si tics such as perf mro ance, u as b ili ty, etc.

rgorP am in ps e oitc ns

F ro silam ed ap rp oach to docum tne re eiv ws. tnI ended xe p il cit yl for defect detection (not c rro ec it on). feD ce st may be lo ig ac l errors, anoma il es ni the c do e aht t thgim ni dic ta e an erroneous cond iti on ( .e g. na u in nitia sil ed variable) ro non-comp il an ec iw th ts andards.

psnI e itc on rp e- oc dn it oi ns

• A rp ec si e spe ic fication mu ts be ava ilable. • aeT m memb re s mu ts be af m aili r iw th the ro ag n si ation ts anda dr s. • S ny tact ci ally correct code ro o ht er s tsy em repr ese nta it o sn mu ts be

ava li ba el . • nA e rr or hc ec tsilk hs oul b d e prepared. • aM na eg me tn mu ts accept taht i sn pe itc on w lli cni re sa e co sts early

ni eht so wtf are pro ec ss . • aM na eg me tn hs ould not u es sni pec it o sn for ts a ff appr sia al i.e.

f ni ding out hw o m seka sim tak se . Th i e n eps ct noi orp ces s

I In ps e itc on corp e rud e

• S tsy em over iv ew rp ese tn ed to sni pec it on team. • oC de and a ss o ic ated od cume stn are d tsi ribu et d to sni p ce tion team in advance. • I sn p ce it on ta sek pla ec and d csi overed errors are on ted. • oM difi ac tio sn are made to repair d csi o ev red rre ors. • eR -inspe itc on may or may not be r qe uired.



psnI e itc on ro sel

Au oht r or owner The programmer or designer resp no sible for produc ni g the pr go ram or document. Responsible for fixi gn def ce ts discovered during ht e ni specti no process.

nI sp ce t ro Finds errors, om si sions and inco sn istencies ni programs and documen st . May also identi yf broader si sues that are out is de the cs ope of the inspect oi n t ae .m

Reader P er sents ht e c do e or document at an ni specti no meetin .g

cS ribe eR cords the re us l st of the inspec oit n m ee ting.

Chairman or moderat ro Manages the process and facilitates ht e insp ce ti no . eR op str proc sse re us l st to the Chief moderator.

Chief moderat ro Resp no is ble for inspec oit n process improvemen ,st checkli ts pu datin ,g standa dr s d ve e ol pme tn et .c

In ps e itc on hc ec lk ist s

• Check tsil of co mm on errors hs uo ld be u es d to dr evi the inspe itc on. • Err ro chec lk ists a er progra mm gni la gn ua eg depende tn and re lf ce t eht

c ah r ca et r si t ci errors ht at are kil ely to ra si e ni t eh al ngua eg . • In general , eht ' ew a ek 'r t eh type ehc ck gni , ht e al rger eht ehc ck tsil . • Example :s I in tia asil tion, Co tsn ant an m gni , loop term ni ation, array

bound ,s etc. Ins c noitcep h kce

aD ta fa lu ts era la l pro marg airav lb es i in tiali dez before t rieh av ul es are us de ? Have all noc st na ts neeb na em d?

hS ould t eh l rewo bou dn fo rra ays be 0, 1, ro

so em th ni g le se? hS ould t eh upp re bou dn fo rra ays be e uq la

to t eh size fo the yarra ro S ezi -1? fI ahc ar ct re stri gn s are ,desu is a led i im t re

expli ic tly assign de ?

Cont lor fa lu st rof ea hc co idn t oi an l ts at neme t, is t eh oc nditi no

roc r ce t? sI hcae l oo p rec tain to termi an t ?e



Are com op und ts at neme st roc r ce tly ekcarb t de ?

nI ac se stat neme ts, are a ll p so si lb e ac ses occa unt de f ro ?

Inpu /t o ptu u i lla era stluaf t n selbairav tup us de ? Are a ll uo pt ut av r ai lb es sa s ngi de a av l eu

eb fore t yeh are uo t up t?

nI t re f eca fau tl s od all fu cn ti no a dn p decor ure ac lls ah ve t eh roc r ce t numb re fo p ra a em t sre ?

oD of r am l a dn actual rap a em t re types

am t hc ? Are t eh p emara t re s in ht e r gi ht ro d ?re fI moc pon ne st a ecc ss hs ar de omem r ,y do

t yeh have t eh sa em om del fo the s ah r de omem ry ts ructure?

eS g nem t fa lu st fI a l ni dek ts ructure is mo fid i de , ah ve all

li kn s b ee n roc r ce tly r ae ssign de ? fI yd n ma ic st ro a eg is us de , ah s ps a ec b nee la l aco t de roc r ce tly? sI spa ec exp il ic tly de-all aco t de fa t re ti is on ol ng re snI p ce ti no skcehc requir de ?

ecxE tp noi M na a nemeg t Have all possi lb e re r ro c no id ti no s b nee

tak ne ni to a occ unt?

psnI e itc on ra et

500 ts ate nem t h/s our du gnir over iv ew. 125 os urce ts atem tne /hour during ni d ivi dual

preparatio .n 90-125 tats eme stn /hour ac n be inspe tc ed. snI pe itc on si t eh refore na expen vis e pro ssec . snI pec it ng 500 lines co sts ab uo t 40 ma h/n ours e ff ort -

about 2£ 800 at UK rat se . Automa et d ts atic ana yl sis

• tS a it c an la sy re s are so tf ware ot o sl f ro os u cr e te tx pro issec ng . • They par es ht e program te tx and try to d si cover potentially erroneous

cond iti o sn and br gni th se e to eht at net tion of ht e V & V team . • They are ev ry effect vi e sa an aid ot sni pec it o sn - ht ey are a us pp el me tn

ot ub t not a rep cal ement f ro sni pec it o sn . Stag se o f static analysi s

• Co tn or l lf ow na alys si . hC ec sk for ol po s iw th um itl p el ex ti or e tn ry po stni , f ni ds unre ahca ble code, etc.



• taD a use a an lys si . Detects un ini tia esil d av riab sel , av r ai b sel wr ti ten tw ci e without an ni ter ev ning ass ngi me tn , av r ai bles ihw ch a er declared but ne ev r used, cte .

• I tn er af ec na alys si . ehC cks ht e c no tsis ency of r uo nit e and proce ud re de alc ar it o sn na d ht eir u es .

• I fn orma it on flow an la ys si . Id ne tif sei ht e depende icn es of ou pt ut av riables. Do se not detect na mo a il es sti e fl b tu ih g lh i sthg ni fo mr ita on

f ro oc de sni pe itc on ro review • Pa ht analys si . Identifies pa sht throu hg ht e program and es ts out eht

st ta eme stn e ex cuted ni ht at p hta . Aga ni , po itnet ally useful ni the review pro ssec

• Bo ht seht e ts ages ge en rate v tsa amou stn of informa it on. They mu ts b e used w hti care .

LINT ats t ci anal sy is

1 83 % more li tn _ xe . c # ni clude < ts dio. >h

rp tni a rr ay (Ana rr ay ) tni nA a rr ay ;

{ rp ftni (“%d”,Ana rr ay); }

m nia )( { tni nA a rr ay[5 ;] tni i ; char ;c

rp tni a rr ay (Ana rr ay, i, c); rp tni a rr ay (Ana rr ay) ; }

1 93 % cc tnil _ex.c 1 04 % tnil l tni _ xe .c

tnil _ex.c(10): war in n :g c may be used bef ro e set tnil _ex.c(10): war in n :g i may be u es d b fe ore tes

rp ni ta rr a :y var ai ble # of ar sg . tnil _ xe c. 4( ) :: tnil _ex c. 1( 0) rp tni a rr ay, arg. 1 used ni cons tsi ently li tn _ xe c. (4) ::

tnil _ex.c(10) rp tni a rr ay, arg. 1 used ni cons tsi ently li tn _ xe c. (4) :: IL NT ts atic analysis tnil _ex.c(11)

rp ftni r te ur sn value w hcih si alwa sy igno er d.

esU fo s a citat nal isy s Par it cularly valuab el hw en a language such sa C is used ihw ch has ew ak typ gni and cneh e many re ror s are unde cet te d by the comp li er, sseL cost- fe f ce t vi e for la gn uag se like Java aht t have ts ro gn yt pe chec ik ng and ac n ht erefore de et ct many e rr ors during comp li ation.



ireV f ci a noit a dn for lam em th do s • oF rm la methods c na be used nehw a mathemat ci al specifica it on of eht s sy tem si pro ud c de . • They a er the ultim ta e ats tic ev rif ci ation et ch in que. • They vni o evl deta li ed ma eht m ita ac l analys si of ht e specific ita on an d may dev le op of rm la gra um ne ts ht at a program co fn orms to sti mat eh m ta ical spec ifi ac tion .

Argume stn fo f r ormal tem hods

rP oduci gn a ma eht mati ac l sp ce if aci tion re uq ir se a det elia d anal sy is of eht requi er me stn na d siht si kil ely to uncov re errors. hT ey ca n det ce t i pm el me tn ation errors before itset ng hw en the program si analyzed alongside eht sp ice fication.

grA u em nts a niag s tem lamrof t h do s

• eR qui er specia il ez d nota it o sn that ca nn ot be unde tsr ood by dom nia experts. • eV ry expe sn ive to d leve op a spe ic f ci ation and e nev rom e expens vi e to hs ow taht a program em e st aht t spe ic f ci ation. • tI m ya be op iss ble to re ca h eht same level of co fn id ecne in a program om re ch ae ply usi gn o ht er V & V tech in uq se .

aelC n moor s ved erawtfo e ol p em n t T eh man e si der evi d from ht e ‘ lC e na roo ’m pro ssec ni es miconduc ot r fa rb itaci on. The

p lih o os p yh si d fe ce t avoidance ar ht er than de ef ct er om lav . T sih so wtf are develo mp e tn proc sse si b sa ed on: • Increme tn al developm ;tne • oF rm la sp ce ification; • tS a it c v re ifi ac tion u gnis c rro ec nt e ss arguments; • tS a sit tical test gni to d te e mr ni e program re il ab ili ty.

The aelC n moor p cor ess

I

lC ae n moor p cor ess arahc c iret s cit s • oF rm la sp ce ification usi gn a ats te trans iti on mod le .



• Increme tn al developm tne ehw er the cu ts omer rp io ir t si es cni reme tn s.

• rtS uctured progra mm gni - il m ti ed co rtn ol na d ab ts ar ction co sn t ur c st are u es d ni ht e prog ar m. • tS a it c v re ifi ac tion u gnis r gi or uo s sni pec it o sn . • tS a sit tical test gni of eht s tsy em

Fo lamr sp cifice a oit n na d ni ps noitce s

• The ts ate based om del si a s sy tem sp ce ifica it on and eht sni pe itc on rp oce ss chec sk the prog ar m aga tsni ht is m do e. l

• The progra mm gni approa hc si de nif e d so taht eht corre ps ond cne e betw ee n ht e om d le and eht s tsy em si lc .rae • M hta emat ci al arg mu ne ts (not p or o sf ) are u es d ot ni crease confiden ec ni eht i sn pec it on pro ec ss .

aelC n moor p cor ess smaet Specif ci ation team : seR po isn b el for d ve elop gni and m nia tain gni t eh sys et m sp ce if aci tion.

veD elopme tn t ae m : Re ps o isn b el for developing and verif gniy t eh so wtf are. The so tf eraw si TON xe ce uted or neve comp eli d ud ring th si proce ss . C re acifit tion et am: seR op isn b el for d leve op gni a es t of st sita t ci al te sts to xe er ic se ht e so tf ware fa ter devel mpo tne . ileR ab ili ty g or htw mod sle u es d to d te re m eni when r ile abi il ty si ac ec ptab el .

aelC n moor p cor ess ulave a it o n

• The resu tl s of u gnis eht Cle na room proc sse ha ev be ne very i rpm e eviss iw th few d si covered faults ni de evil red syste sm . • Indep ne de tn a ss es ms e tn sho sw ht at the proc sse si no more expens vi e ht an o ht re a pp ro ca seh . • Th ere ew re fe ew r errors naht ni a t' rad iti ona 'l devel mpo tne proc sse . • However, eht rp oce ss si not iw dely used. tI si not elc ar how th si approa hc ac n be tr fsna e rr ed to na ne vironme tn iw th le ss ski ll ed ro le ss mo avit te d so tf eraw engin ee rs.

The et ts in g p ecor ss moC ponen et t s it gn

• T tse i gn of ni d ivi dual rp ogr ma co pm one stn ; • sU ually the r se op isn b ili ty of ht e c opmo tnen d ve elop re ( ecxe pt some it m se for cr iti cal s tsy ems); • T stse are der vi ed from eht d leve ope ’r s experience. S tsy e t m e gnits • T tse i gn of groups of compone stn tni egrated to erc ta e a s etsy m or sub-s tsy em; • The respo isn b ili ty of na ni depend ne t test gni t ae ;m • T stse are ba es d on a metsys spe ic f aci tion.


S fo wt are E ign nee ir ng 10 SI 51 I eT s ahp gnit s se

\

et tcefeD s gnit • The goal of d fe ect te gnits si to d csi over de ef c st ni programs • A succe fss ul d fe e tc tset si a te ts ihw ch cau ses a p gor ram to be ah ve ni an anomalous way • T stse hs ow t eh rp ese cn e not eht ab nes ce of d fe ce st

eT s secorp gnit s og a sl

ilaV dat oi n et s it n :g oT demo sn tr ta e to ht e de lev oper and ht e s sy tem cu ots mer ht at the soft aw re mee st its re uq ireme ;stn a suc ec fss ul te ts sho sw ht at ht e s sy tem oper seta as tni ended.

tcefeD tes it n :g To d si cover fau stl ro def ce st in eht so tf w ra e ehw re its b he a iv or si cni orr ce t or not ni co fn mro an ec with its specifica it o ;n a su ecc ssful

tset si a te ts taht makes eht s sy tem perform incorr ce tly and so ex op ses a d fe e tc ni the sys et m.

T eh s wtfo a et er s nit g secorp s

I

eT s it n g p eicilo s nO ly e hx au evits set ti gn ac n show a prog ar m si free f or m de ef c st .

Ho ew ver, e hx au vits e test gni si mi po iss b el , eT gnits po il cies d nife e t eh ap rp o hca ot be used ni s le ce ting s sy te m

te ts s: • llA fu cn tio sn accessed thr uo hg menus should be t tse ed; •Comb ani tions of func it o sn a ecc ssed ht rou hg ht e same nem u hs ould be te ets d;



• hW ere u es r ni put si r qe uired, lla functions um ts be tested w hti correct na d cni o rr ect ni put. et metsyS s gnit • I vn o sevl i tn egr ita ng compone stn to erc ate a s tsy em or us b- sys et m. • M ya invo evl set ti gn na ni creme tn to be d ile v re ed to eht cu ts omer. • T ow phase :s Int ge ration testing - ht e te ts te ma have ac ec ss to ht e s sy tem source cod .e The s sy tem si tset ed sa com op nents are etni grated. Re el ase test gni - the te ts te ma t tse ht e co pm tel e sys et m to be de vil ered sa a black-box . Int ge ration testing • I vn o sevl bu li ding a s tsy em from sti com op stnen and te its ng ti f ro rp bo lems ht at ar esi from compone tn i tn eracti no s. Top- od nw ni t ge rati no : Develop ht e skeleton fo ht e s etsy m and popu tal e ti iw th compone stn . Bottom-up tni egratio :n I tn egrate infrastru utc re oc m op stnen t neh add fu cn tional co pm onents . • To is mp il fy error loca sil ation, s etsy ms hs ould be ni creme tn all y

tni egra et d. Incre em n i lat n oitarget n et s it n g

I

eT s it n pa g p caor h se • Arch ti e tc ural ilav da it on: Top-do nw tni eg ar tion t se ting si be tt re at d si cover gni re rors ni t eh s etsy m arch ti ect ru e. • S tsy em de om tsn rati no : Top-down tni egra it on testing a ll ows a il m ti ed demo sn tr ita on at an early sta eg ni the d ve elopment. • T tse mi plementation: fO ten easier with bo tt om-up tni egration te gnits . • T tse obser itav on: Pr bo el ms htiw bo ht a pp roa hc es. E tx ra c do e m ya be re uq ired to obs re ev t stse .



set esaeleR tin g • The proc sse of itset ng a er le sa e of a s tsy em t tah wi ll be d si tribu det to cu ts omers. • Primary goal si to cni rease ht e supp il re ’s confiden ec taht ht e sys et m mee st its re uq irem stne . • leR ae es set ting si usu la ly black-box or fu itcn o lan test ni g • saB ed on ht e s sy tem specification only; • T tse ers do not ha ev kno lw ed eg of ht e s tsy em i pm lem tne ation.

alB ck- xob et s gnit

I

eT s g gnit u iledi n se eT gnits guide nil es are stnih for eht t itse ng team to leh p eht m hc oo es

te sts aht t wi ll er veal d fe ce st ni eht sys et m • hC oose ni up ts ht at for ec the s sy tem to eg ne ar et a ll err ro m sse ages ; • Design ni pu st ht at cau es buf ef rs to ove fr low ; • eR peat the same ni put or ni put se seir se ev ral emit s; • oF r ec inva il d outp stu to be ge en rated; • oF r ec c pmo uta it on results ot be too al r eg ro ot o ms a ll .

yS stem te sts 1 . T e s t t h e l o ni g e m c a h n i s m u s i n g c o r r e c t a n d i n c r o er t c l o s ni g to c h e c k

t a h t d i l a v sr e s u e r a d et p e c c a d n a i l a v n i d sr e s u er a . d e t c ej e r

2 . t s e T e h t h c r a e s f a i c il t s u y i g n r e f fi d e r e u q t n s ei t s ni a g a n w o n k s e c r u o s ot k c e h c t a h t e ht h c r a e s m s i n a h c e m si yl l a u t c a g n i d n i f e m u c o d . s t n

3 . T e s t t h e s s y m et er p s e t n a t i o n f a c i l i t y t o h c e k c t h a t i f n o r a m t i o n a b o u t s t n e m u c o d si d e y al p s i d . yl r e p o r p

4 . t s e T e h t m si n a h c e m o t n o i s si m r e p t s e u q e r r o f . g n i d a o l n w o d

5 . T e s t t h e e - a m i l r e s p n o s e i d n i c a t i n g t h a t t h e o d n w l o a e d d d c o n e m u t i s a v a i l a b l e .



Use cas se esU cases can be a ba sis for der gnivi t eh tests f ro a s etsy .m The y

help id itne fy oper ita o sn to be te ts ed and leh p d ise gn ht e requir de te ts sac es. From an a ss ocia et d qes u ne ce diagram, ht e ni puts na d out up st to be crea et d for eht stset can be id itne fied.

C htaew tcello er d ata s qe uen hc ec a tr

I

Pe cnamrofr e itset n g

P ra t of rele esa testing may i vn o evl testi gn eht em re ge tn pr po er it es of a tsys em, such as perfo mr ecna and re ail b ili ty. eP rforman ec te sts usu la ly i vn o evl plan in ng a series of stset wh re e the loa d si ts eadily

cni rea es d u litn eht s sy tem perf ro ma cn e b ce omes nu ca ceptab el .

ertS ss et s it n g • Ex cre si es eht s sy tem beyond its ma mix um de ngis load.

tS re gniss the s tsy em o netf causes d efe cts to come ot thgil . • tS re ss i gn the s etsy m tset f lia ure behaviou ..r S tsy ems hs ould no t fa li ac tsat rop ih ac lly. tS re ss set t gni chec sk for unaccep at b el lo ss fo es vr ice or da at . • tS re ss tset i gn si par cit u al rly r le eva tn t o d tsi ribu et d syste sm that c na exhib ti ves re e degrada it on sa a

wten ork beco sem overloaded.

moC ponen et t s it n g • Co pm onent ro u tin testing si t eh pro ec ss of te its ng ind ivi dual co pm onents ni si olation.



• tI si a d fe ce t te its ng p or ec ss . • Co pm onents may be: • Ind ivi dual functio sn ro me ht do s iw t nih an ob ;tcej • Object alc sses iw th eves ral a tt ribut se and me ht od ;s • Co pm o etis co pm onents iw th de nif ed ni terfac se u es d to ac ec ss

ieht r fu cn tiona il ty.

salc tcejbO s itset n g Comp el te t tse coverage of a alc ss invo vl es • T tse i gn lla oper ita o sn ssa o taic ed htiw an obj ce ;t • Se itt ng and tni e orr ag t gni a ll ob ej ct a tt ribute ;s • Ex cre is gni eht bo tcej ni a ll po iss b el ts ates. I ehn r ti ance mak se ti rom e d fi ficu tl to d ngise ob cej t alc ss te sts as t eh info mr ation to be te ts ed si not lo silac ed.

htaeW e r s o noitat b ej c i t n fret a ec I

htaeW e r s et noitat s gnit •Need to d nife e tset c sa es for re rop tW ehtae ,r ca il bra et , te ts , ts artup and hs u dt o nw . • isU ng a ts ate om d le , id itne fy es que cn es fo ats te tr na sitio sn to be te ets d na d eht ve e tn sequenc se to cause seht e tr na sitions F ro exa pm le: •Wai it gn -> Ca il bra gnit -> T tse i gn -> Tr timsna t gni -> Wa iti ng.

fretnI a et ec s it n g • Object vi es are ot de et ct fau stl ud e to tni re fa ec e rorr s or vni a il d a ss ump it o sn ab uo t etni rfaces.



• P ra it cularly impor tnat for bo je tc -orie tn ed d ve elopme tn sa objects are d nife ed by ht eir i etn rfaces.

I ecafretn et sting

I

I ecafretn ty ep s

• P ra ame et r ni ter caf es: D ta a pa ss ed from o en rp ocedure to ano ht e .r • hS ared mem ro y ni terfaces: lB ock of memory si sh ra ed b te ew ne procedu er s or fu cn tio sn . • rP o ec d ru la etni rfa ec s: S bu -s tsy em e acn psu tal es a s te of procedu er s to be ac ll ed by o ht er us b- tsys ems. • M sse a eg p issa ng etni rfaces: Sub- smetsys reque ts services from other us b-s tsy ems

I ecafretn srorre

• I tn re f eca m si use: A ac ill ng com op tnen ac sll na o ht re c mo op ne tn and ma sek an e orr r ni its u es of sti tni er af ec e.g. p ra ameters ni the w or gn order. • I tn re f eca m si und re ts and :gni A ca ill ng com op tnen e bm eds a ss ump it o sn ab uo t eht be ivah our of the called compo tnen w ih ch are

cni orrect. Dep ra tme tn of CSE, S BJ IT P ga e 86


• Tim gni e rr or :s The c ella d an d eht illac ng compone tn operate at d effi rent sp ee ds an d uo t-of-date fni o mr ation si ac ec ess d.

Inte afr c itset e n g gu iledi n se

• Design stset so ht at parame et rs to a ac ll ed rp o dec ru e are at the e tx reme ends of ieht r ran seg . • wlA a sy tset po ni ter p ra ame et rs htiw null po tni re s. • Design stset w ih ch cau es ht e compone tn to fa li . • sU e ts re ss test gni ni m sse age pass gni s sy tems . • In s ah er d mem ory s tsy ems , vary t eh order ni which co pm o stnen are ca avit ted.

eT s esac t d ngise

• I vn o sevl d se ign gni the tset cases ( ni p stu na d uo pt u st ) used ot te ts eht s tsy em. • The goal of te ts c sa e d ise gn si to cr ae te a tes of t stse ht at are eff ce t evi ni va il d ita on and defe tc set t ni g. • Design approaches: • eR qui er m stne -based te its ng; • P ra itit on t se ting ; • rtS uctur la te gnits .

emeriuqeR nts ab s et de s gnit

A ge en ral pr ni ciple fo re uq ireme stn en enig ering is ht at requi er m stne hs ould be tset ab el . qeR uireme stn -b sa ed gnitset si a lav id ita on

te gnits technique where you co isn der each requireme tn and d re vi e a es t of stset of r ht at requirement.

IL BS SY uqer i mer e tn sL BI SYS et sts

The user shall be able to search e ti eh r a ll fo the ini it al set of dat ba ases or es lect a sub es t from .ti

The s sy tem shall provide appropr ai te viewers for the user to read docume tn s in the od cument ts ore.

Every order hs a ll eb all co ated a unique iden it fier (ORDER_ID) that the user shall be ab el to copy to the accountÕ


s permane tn st ro age a er a.


Pa oititr n et s gnit

• Input d ata dna ou pt ut r se ults o netf af ll tni o diff re e tn lc as ses hw re e all members of a ssalc are re etal d.

• E hca of eseht alc s ses si na equ lavi e ecn par itit on or od m nia hw re e t eh progr ma be sevah ni an equ tnelavi way for hcae c ssal

member.

• nI iti a et u res search for searc seh for it me s ht at are wonk n to eb pre es nt na d wonk n n to ot eb presen ,t hw ere ht e es t of

batad ases dulcni es 1 da bat as .e • nI iti a et u res searc seh fo r ti ems ht at ar wonk e n t o be rp se e tn

na d wonk n n to ot be pre es nt, hw ere t eh se t of da bat as se cni l du es 2 da bat as se

• nI iti a et u res searc seh fo r ti ems ht at ar wonk e n t o be rp se e tn na d wonk n n to ot be pre es nt hw ere ht e tes of da at bases cni l du es om re t ah n 2 dat ba ase .s

• eleS ct eno data esab f or m t eh s te fo dat aba ses and in iti a et su e s r ea cr h f se or items taht ar wonk e n t b o e pr ese nt dna nk own not ot be prese .tn

• eleS ct m ro e t nah one da at ba es from the s te fo data sab es na d i itin ate sear hc es for items ht at are nwonk t o eb present na d wonk n n to ot be pre es n .t

• T tse sesac hs ould be hc o nes from hcae part iti on . E viuq a el n ec pa ninoititr g

I

Dep ra tm tne of CSE, S BJ IT P ega 88


E viuq a cnel e pa titr i no s

I

Sea enituor hcr spe cific a noit

pro ec dure Sear hc (Key : ELEM ; T: SEQ of E EL M; Found : ni uo t LOOB E ;NA :L ni out EL ME _ DNI EX) ;

Pre-cond iti on

-- eht sequ ecne has at sael t o en ele m ne t T’ SRIF T <= ’T TSAL

Po ts -cond iti on -- eht le me tne si fou dn na d si r fe re ne ced by L ( Fou dn na d T ( )L = Key)

or -- eht le me tne si not ni the a rr ay ( not oF und dna not ( stsixe i, T’FI SR T => i =< T’ SAL T, T (i) = yeK ))

Se cra h or u it n e - inpu trap t i snoit

• Inpu st hcihw co fn orm to ht e pre-cond iti o sn . • Inpu st ehw re a pre-cond iti on does not ho dl . • Inpu st ehw re ht e key eleme tn si a me bm e fo r eht rra ay. • Inpu st ehw re ht e key eleme tn si not a m me ber of eht array.

eT s it n g g u iledi n qes( se uen ec s )

• T tse so awtf re htiw es qu ne c se which ha ev only a s ni g el value . • sU e es qu cne es of d effi re tn sezis ni d fi fer tne set ts . • eD r evi set ts so taht eht if rst, m di d el and tsal le ements of t eh es qu cne e are ca c esse d.

• T tse htiw seque secn of z re o el ngth.



craeS h or u it n e - inpu p t art noiti s

Se q uence El e me nt Single value In sequence Single value N ot in sequence

M ore than 1 value F irst ele m ent in seque cn e M ore than 1 value Last ele m ent in se uq ence M ore than 1 value M iddle ele m ent in sequence M ore than 1 value N ot in sequence

Input se uq ence (T ) K ey ( K ey) t u O put (Found , L ) 17 17 true, 1 17 0 false, ?? 17, 29 , 12 , 23 17 true, 1 41, 18 , 9 , 31, 30, 16, 45 45 true, 7 17, 18 , 12 , 23 , 92 , 41 , 38 23 true, 4 21, 23 , 92 , 33 , 38 25 false, ??

rtS u tc u et lar s it n g So item me ellac d etihw -box itset ng. D re iv ita on of tset sac es according to program rts u tc ru e. nK o elw dge of the program si u es d to ide itn fy add iti onal tset sesac . Ob ej c it ve si t o xe er esic a ll progr ma ts a et me stn (not lla p hta comb ani tio sn )

I

aniB r y s crae h - equ vi . pa snoititr • Pre-cond iti o sn as tis eif d, key eleme tn in a rr ay. • Pre-cond iti o sn as tis eif d, key eleme tn not ni arr ya . • Pre-cond iti o sn u sn a it s eif d, key eleme tn in array. • Pre-cond iti o sn u sn a it s eif d, key eleme tn not ni ra ray. • Input rra ay has a nis gle value. • Input rra ay has na ve en numb re of lav ues.



• Input rra ay has na odd numbe fo r values

I

aes yraniB r hc - te ac ts s se

Input array (T) Key (Key) O tu up t ( ,dnuoF L) 17 17 tr ,eu 1 17 0 false, ?? 1 ,7 21, ,32 92 17 tr ,eu 1 9, 1 ,6 ,81 ,03 ,13 ,14 54 45 tr ,eu 7 1 ,7 18, ,12 ,32 ,92 ,83 41 23 tr ,eu 4 1 ,7 18, ,12 ,32 ,92 ,33 38 21 tr ,eu 3 1 ,2 18, ,12 ,32 23 23 tr ,eu 4 2 ,1 23, ,92 ,33 83 25 false, ??

Path gnitset

• The ob ej c evit of p hta te its ng is to sne ure aht t eht tes of te ts c sesa si such t tah ae ch path throu hg t eh program is e ex cu et d ta tsael o ecn . • The ts ar it ng po tni for p hta itset ng si a program lf ow graph aht t hs o sw nodes re rp nese ting progr ma de ic sio sn na d ar sc repre nes ting eht flow of co tn or l.

• metatS ents iw th cond iti o sn are eht r fe ore on d se ni the flow arg ph.



raniB y s olf hcrae w hparg I

Indep p tnedne ath s

• ,1 2, 3, 4, 5, ,6 7, 8, 9, 10, 14 • ,1 2, 3, 4, 5, 14 • ,1 2, 3, 4, 5, ,6 7, 11, 12, ,5 … • ,1 2, 3, 4, 6, ,7 2, 11, 13, ,5 …

• eT ts ca ses sh uo dl be der evi d os ht at a ll of t eseh p shta are e cex u det •A d any m ci program na alyser may be used to kcehc that p shta have been e cex u et d

eT s noitamotua t

• T tse i gn si an exp ne s evi proce ss pha es . T tse i gn wo kr b ne ch se pro iv de a ra egn of t oo sl to re ud ec eht t emi required na d total t itse ng co ts s. • S etsy ms such sa Ju tin support eht aut mo a it c cexe u it on of stset . • Mo ts tset i gn workbe sehcn are op ne s sy tems b suace e te gnits

een ds are orga sin ation-sp ice fic. • They are some it mes d fi f ci ult to tni egra et iw th lc o es d d ngise and na alys si workb hcne es.



gnitset A w kro ben hc I

eT s it n krow g b ne ch ada pta it o n • S rc ip st may be de lev po ed for u es r etni rf eca mis ulat ro s and p tta re sn f ro t tse d ata neg re ta ro s. • T tse ou pt u st may evah to be rp epared nam ually f ro compar si on . • Sp ce lai -pu pr o es f li e co pm ar ota rs may be de lev op de .



UNIT – 8 MA EGAN MEN T

aM na ig n g p oe p el • M na a ig ng p oe ple wor gnik sa ni dividu sla na d ni groups • To xe p nial s mo e of t eh i ss u se invo evl d ni se el cting na d re at i in ng sta ff • To d se rc ibe tcaf ors taht lfni uence ni d ivi du la mo avit tion • To d csi u ss key ssi u se of aet m wo ikr ng i lcn uding com op itis on, co eh s nevi e ss na d co mm u acin ti no s • To tni roduce eht pe po le capability maturity model (P- )MMC - a fr ma ew ro k for hne a icn ng eht ac pabilities of p oe ple ni na

ro zinag ation . Peop i el n th e p secor s

Peop el are na orga zin ation’s om ts mi por tnat tessa s. T eh sksat of a m na a eg r are nesse tially pe po el -or etnei d. lnU e ss t eh re si so em und re nats d ni g of peop el , ma egan me tn iw ll be u sn u cc e fss ul. oP or peop el m na agem tne si an i pm o tnatr co tn ribut ro to pro tcej liaf ure.

Peo lp am e na emeg n rotcaf t s

Cons tsi enc :y T ae m members ohs uld lla be tr detae ni a comparab el yaw without favor ti es ro d csi rim itani on.

Resp :tce Diff re tne t ae m em bm ers evah dif ef r tne sk slli and eseht d effi renc se should be resp detce . Inclu is no : nI vo vl e a ll aet m me bm ers na d m ka e sure aht t pe po le’s

eiv ws ra e co isn dered. Honest :y You ohs u dl wla a sy be ho tsen about tahw si go gni we ll na d

tahw si go gni bad yl ni a pro tcej .

gnitceleS s ffat nA mi p ro ta tn pro ej ct m na ageme tn task si et am se itcel on.

I fn orm ita on on les e itc on com se fro :m • I fn orma it on pro iv ded by t eh nac did seta . • I fn orma it on ga ni ed by tni e vr ei w gni an d klat i gn w hti c na dida set . • eR comm ne d ita o sn and comm stne from o eht r pe po le hw o nk ow or hw o vah e worked htiw eht ac ndidates.

itavitoM n p g eop el

nA mi p ro ta tn ro el of a m na ag re si to mo vit a et t eh p oe ple wor ik ng on a pro tcej . Mo avit tion si a comp xel issue ub t ti pa p ae rs taht eht re are d effi ren t types of mo avit tion base d o :n • aB s ci een ds (e.g. food, ls ee p, etc. ;)



• P re so lan needs (e.g. r se p tce , les f- tse eem); • Soc lai n ee ds (e.g. ot be cca ep det sa part of a rg oup).

muH a n n e de s hi re a yhcr

I

\

eeN d itas s af c noit So laic • rP o iv de co mm u lan faci il ties; • Allow fni mro la commu acin ti no s. E ts eem • eR c go itin on of ca hie mev e stn ; • Appropr tai e r awe rds. • Se fl -r azilae tionTr ia n gni - peop el wa tn to ael rn

rom seR;e op isn bi il ty

reP s ilano t y t py e s T eh needs hier ra chy si al om ts ec r niat ly an o ev r- is pm il fic ita on of

om avit tion ni pr itca .ec Mo avit tion should sla o t eka ni to ca c uo tn d ffi er tne persona il ty types: • T ksa - ro ie etn d; • Se fl - ro etnei d; • I tn er ca tion-oriented.

T ksa -or tnei ed. • The om avit tion for od ing ht e work si the work itse fl ; Se fl -or tnei ed.



• The work si a means to na end cihw h si the ca hiev me tne of ni dividu la goa sl - .e g. to teg rich, to play ten sin , ot tr va el te .c ;

Inter ca tion-or etnei d • The pr ni cip la mo avit tion si eht rp e es n ec na d a itc o sn of co- wor ek rs. oeP p el go to ow rk becau es yeht ekil to go to w ro k.

oitavitoM n ba al n ec

Ind ivi du la om avit tio sn are am de up of e el m stne of hcae lc a ss . T eh b la a cn e can cha egn dep ne ding on perso lan circumstances and etxe r lan events. Ho evew r, peo elp ra e not ju ts

om etavit d by perso lan factors but sla o by being part of a group na d cu tl ure. Pe po el go to w ro k b ce au es they are om tavit ed by ht e peop el taht ht ey w ro k iw th .

naM a ig n org g u sp Mo ts so awtf re ne g ni ee r gni si a g uor p itca vity • The d leve opment hcs e ud el for most non-tr ivi al so awtf re projects si such t tah they ca nn ot be comp el ted by one perso n wor gnik la o en . Group tni er ca tion si a key d ete rm ni a tn of g or up performa ecn .

lF exib ili ty ni group co pm o is tion si lim eti d • M na a eg rs mu ts do ht e b tse ht ey can with ava li ab el pe po l .e

Fa lfni srotc u gnicne uorg p w ro kin g

• Group co pm o itis on. • Group co eh s vi ene ss . • Group commu acin tio sn . • Group or zinag ation.

orG u moc p pos oiti n

Group com op des of m me bers hw o ahs re eht mas e om t avi tion can be prob el m ita c • T ksa - ro ie etn d - e ev ryo en naw ts to do ieht r o nw gniht ; • Se fl - ro etnei d - e ev ryo en wa stn to be ht e bo ss ; • I tn re ca tion-oriented - too mu hc c tah ti gn , not one u hg w ro k .

nA eff ce t vi e group has a b la ance of a ll typ se . Th si nac be d fi ficu tl to ca hieve so awtf re ne g ni eers are o netf ksat - ro iented. caretnI tion-

ro etnei d p oe p el are ev ry i ropm tnat sa they can dete tc na d defu es isnet o sn that ar esi .



orG u moc p pos oiti n In creating a group for as is stive technology development, Alice is aware of the importance of sel ce ting members with complementary personalities. When interviewing people, she tried to assess whether they we er task oriented, self- oriented and interact oi n oriented. She felt that she was primarily a self-orie tn ed type as hs e felt that this project was a way in hw ich she would b e n oticed b y senior management and promoted. She therefore looked for 1 or perhaps 2 interac it on- oriented persona il ties with the rema ni der task oriented. The final a ss essment th ta she arrived at was: Alice Š les f-oriented Brian Š task-oriented Bob Š task-orient de

aC rol Š inte ar ction-orient de Dorot yh Š self-oriented Ed Š i tn er ca tion-oriented Fred Š task-oriented

orG up redael sh pi aeL dership dep ne ds on respect not tit u al r ats tu .s T eh re may be ob ht

a tech cin al and na ad tsinim rat evi ael der. meD ocra it c ael der ihs p si rom e effe ct vi e ht at autocra it c leadership.

ehoc puorG s ssenevi

In a cohes vi e group , memb re s co isn der eht group to be mo er i pm orta tn than any ni d ivi ud la ni ti . T eh advanta seg of a co iseh ve group ar :e • Group uq ila ty ts andards nac be developed; • Group m me bers work lc o es ly to eg t eh r so in ih bitio sn cau es d by ignor ecna ra e r de u ec d; • T ae m m me b re s ael rn f mor ae ch oth re and teg to nk ow hcae other’s w ro ;k • Ego ssel programming w eh re m me bers st evir to i pm rove ea hc other’s programs c na be prac esit d .

eT a m spi tir

gnipoleveD c eho s enevi s s

Co seh ivene ss si influ ecne d by caf tors such sa eht orga in zational cu tl ure na d eht p sre ona il t sei in t eh g or up. Co iseh v ssene can be e cn our ega d rht uo hg • Soc lai eve stn ; • leveD op gni a group id itne ty and et rr ti ory; • Exp il c ti aet m-bu li ding activities. Op nne e ss iw th i fn or itam on si a mis p el way of ne s ru gni a ll gro pu me bm ers fe le part of eht group.



orG pu lo eitlay s • Group m me bers net d to be loyal to co eviseh g or ups. • G' ro pu iht nk' si pr se re vation of gro pu irr se p evitce fo cet h in ac l or ro ag nizational consider ita o sn . • M na a eg m tne shou dl act op vitis ely to avoid org upth kni by f ro cing etxe rnal invo evl m tne with hcae group.

orG up moc m nu ci a oit n s

oG do co mm u acin tio sn are sse ential rof ceffe it ve group wor ik ng. I fn orm ita on mu ts be xe cha egn d on eht tats us of w ro k, de ngis decisio sn and hc a segn to pr ive ous dec isi o sn . oG od co mm u itacin no s a sl o ts re gn t eh ns group co iseh on sa ti pro setom under nats ding.

Group zis e: The al rg re t eh grou ,p ht e ha dr re i t si f ro pe po le to c mo mu tacin e with other gro pu m me bers. Group ts ru tc ru e: Commu acin tion is b tte er ni fni mro ally stru tc ru ed groups ht an ni eih rarc ih c la ly ts ur ctured groups. Group com op is ti no : Com um in cation si bet et r nehw ht ere are d effi rent perso ilan ty types ni a group na d nehw groups ra e m xi ed ra eht r ht an sin elg sex. T eh p yh sic la w ro k en iv ro mn ent: G oo d workp ecal organ azi tion can help ne cour ga e co mm u cin a it o sn .

orG up ro gan noitazi

Sm lla sof wt are eng eeni r gni g puor s are usu la ly or ag n ezi d fni orma ll y iw thout a r igi d structure. oF r al rge projects, eht re m ya be a eih rarc ih cal ts ur tc ure ehw re dif ef re tn groups are r pse onsible for

d effi rent sub- rp oje stc . I fn uorg lamro p s

• The group a stc as a hw ole na d co sem to a co sn e sn us on decisio sn fa cef ting the s sy tem. • The group ael der s re ves as eht e etx rnal ni t re face fo t eh g uor p but od se not lla o ac te sp ice f ci work eti ms. • taR he ,r w ro k si d csi u ess d by the group sa a hw o el na d sat ks ra e a ll o ac ted cca ord gni to ab ili ty and xe p re ie ecn . • T sih ap rp o hca si su ecc s fs ul f ro rg oups hw ere lla me bm re s are experie cn ed na d comp tnete .

emertxE p or g immar n g g roups • E tx r me e rp ogr ma ming groups are av r nai ts of na inf ro m la , d me ocr cita or inag za it on. • In e tx reme progr ma mi gn group ,s s mo e m‘ na a eg me tn ’ d ce isio sn are d ve o vl ed to rg oup m me b re s. • rP ogr ma mers work ni pairs na d kat e a co ll e itc ve r se op nsib ili ty f ro c do e taht si d ve eloped.


S fo wt are E ign nee ir ng 10 SI 51 Ch fei p mmargor re maet s

Cons tsi of a ek r len of sp ice a stsil leh pe d by o eht rs added ot eht projec t sa require .d T eh mo avit tion b nihe d ieht r d leve o mp tne si eht

iw de d ffi er ne ce in ab ili ty ni dif ef rent program em rs. ihC e f programm re smaet rp o iv de a supp ro t gni envi or nme tn for very ab el programm re s to be r se op isn b el for mo ts of eht sys tem d leve o mp tne .

orP b mel s

T sih c feih progra mm er ap rp o hca , ni dif ef re tn f mro s, sah b nee su secc sful ni s mo e ttes i sgn . However, ti su ff re s from a number of p or b mel s • T etnela d d ise g en rs an d progra mm ers are ah dr to nif .d W hti uo t excep it o lan p oe p el ni ht e es ro sel , eht ap orp hca lliw fail; • Ot eh r g or up m me bers may r se e tn the ihc ef progr ma m re ikat ng

eht cred ti for su ssecc so may d ile ber eta ly underm ni e h si /her ro ;el • Th re e si a hi hg rp o cej t r ksi sa t eh pro cej t lliw fa li fi bo ht eht c ih ef and deputy progra mm er ar e unava li ab el . • The or azinag tional ts ructur se na d grad se ni a co apm ny may be u an b el to a cc o omm d eta siht type of group.

Wo ikr n e g n oriv n em nts

T eh p yh sic la w ro kpla ec pro iv sion h sa an i pm o tr a tn eff tce on ni d ivi du la produ ivitc ty and itas s caf ti no • C mo fo ;tr • avirP c ;y • Fa ic lit sei .

eH alth an d sa ef ty c no sidera it o sn um ts be kat en tni o ca c uo tn

• hgiL ting; • aeH ting; • uF r tin ure.

En oriv n em nta af l c rot s

Privacy - hcae e enign er requir se na area for u tnin re rupted work. Ou ist de awa re ssen - peop el rp efe r to work ni tan u lar li thg . P re so an l azi tion - ni div di ua sl adopt d effi r tne wor ik ng rp ca t seci and

ekil to or ag nize ht eir environm tne ni d ffi re tne wa sy . Wo kr sp agro eca n zi a noit

Wor sk pac se hs ould rp o iv de pr etavi sp seca ehw re pe po le can work iw thout etni urr ption

• rP o iv d gni ni dividu la of cif es for ffats sah b nee hs o nw to cni rea es p or duc it vity.

However, te ma s w ro gnik toge eht r a sl o re uq ire sp ca es ehw re formal and fni ro m la em e it n sg can be held.



l eciffO ya o tu Th P e eop aC el pab taM ytili u ir t oM y d le

• I tn ended as a fra wem ork for ma an g gni the d leve opme tn of peop el invo evl d ni so wtf are d leve o mp e tn . P- O MMC b ej c sevit • To mi pro ev ro ag nizational ac pab ili ty by mi pro gniv wor fk or ec ac pab ili ty.

• To sne ure taht so wtf are d ve elo mp tne ac pability si not re il a tn on a llams number of ni d ivi ud sla . • To ila gn ht e om t avi tion of ni di iv du sla iw th ht at of eht

ro zinag ation . • To leh p ter a ni peop el iw th crit ci al kno elw d eg na d ks i sll .

P-C MM l leve s

eviF ts age mod le I aitin l. Ad-hoc p oe p el nam a eg ment Repeatab el . Po il cies developed for capab ili ty i rpm o ev m ne t

eD fined. tS and ra di ez d pe po el ma an geme tn a rc o ss ht e or inag za it no M na a eg d. Qu atitna t evi go sla for peop el anam geme tn ni p cal e Op imit zing. Co nitn ou us focus on imp or gniv ni d divi u la comp nete ec and ow r fk ro ce mo avit ti no

Dep ra tm tne of CSE, S BJ IT gaP e 100


elpoep ehT capa tilib y mo ed l

wtfoS are e tsoc s noitamit

uF dn ema nta mitse l a oit n ques snoit • How um hc ffe ort si required ot comp tel e an act ytivi ? • How um hc calendar it me si need de to comp etel na a ivitc ty? • hW at si eht total co ts of an ac ivit ty? • rP o tcej se timation and ehcs du gnil ra e etni r el a ev d eganam me tn a tc i iv t ei s?

wtfoS are tsoc c mo ponen st

aH rd aw re na d so awtf re co sts . Tra lev and tr ia n gni co sts . E ff ort co sts ( eht do nim ant tcaf or ni om ts pro stcej ) • The salari se of ne g eeni rs invo evl d ni the pro ej c ;t • Soc lai and sni ru na ce co sts . E ff ort co sts mu ts kat e over aeh ds tni o ac oc u tn • Co sts of bu li d gni , hea it gn , il ght gni . • Co sts of ne wt or ik ng na d commu acin tio .sn • Co sts of ahs red ilicaf t sei ( .e g. il rb ary, ats ff r tse aura tn , te .c ).

Dep ra tm tne of CSE, S BJ IT gaP e 1 10


itsoC n na g d p icir n g E its m seta are made to d si co ev r eht cost, to eht develop re , of produc gni a so awtf re s tsy .me T eh re si not a is pm le re ital ons ih p b neewte eht developm tne co ts and eht price ahc rged to eht cu ts omer. rB oad re orga azin tional, econ mo ci , op il t laci na d bu enis ss co isn deratio sn in lf u ne ec t eh price ahc r eg d .

wtfoS are irp c ni f g a srotc

a M rket A d e v e lop m ent or g a n isation m ay quote a low p rice b ce a u es it op p ort u nity w ishes to m o v e into a en w s e g m ent of the sof t w a re m ar k e .t

A cc e pting a low pr o fit o n o n e pr o je c t m ay give t h e o p p ort u ni yt o f o m re pr o fit la et r. T eh p xe re c n ei e a g i n ed m ya al lo w n we

or p d u cts to be de v el o p e d.

C o t s e t s i m ta e If an o rg n a i as ti o n is unsure of its cos t esti m at ,e i t a m y in c re a se unc e r yt ni at its pr ci e b y so m e o c nti n ge n cy v o er a nd above i st n o r m al p rofi .t

o C n rt act u a l ter s m A c ust m o er m ay b e w illi n g to al low t h e d ve el o p e r to retain n w o ers h ip o f the so u r c e c o de a d n reuse it in o th e r projects. T h e

r p ice c h arg d e m ay t h en be l se s ht an fi t h e sof t w a re s o urce c e d o i s h n a d e d o v e r to th e c u sto m er.

R e uq ne meri st If e ht re u q i er m e n ts are li k ely to c h a n g e , an organis t a i o n m ay vola t li ity lo w er i st pr ci e to ni w a c o ntr a ct. A f et r the c n o tract is a w ar d ed,

i h gh pric e s c na b e c har deg f o r cha n ges t o t h e requ eri m ne ts.

Fi n a n cial h e a h tl D e v elo p ers in fi n a i c n al diffi c ulty a m y lo w re t h eir p r ice to ga in a c o n trac t . It is b t e ter to m ake a sm aller t ah n n o r a m l p rofit or

b re a k e v en t h an to g o o ut o f b usin se s.

wtfoS are p or ud vitc i yt A m sae ru e of eht r eta ta ihw ch ind ivi dual e ign neers invo evl d ni so awtf re d ve elo mp e tn produ ec sof awt re and a ss o aic ted docum tne a it on. Not qu ila ty-orie etn d htla ou hg uq ila ty ssa ur ecna si a tcaf or ni produc ivit ty a ss e ss me tn . E ss e itn ally, ew wa tn to me sa ure u fes ul fu cn tio ytilan pro ud ced per it me u tin .

dorP u ytivitc me sa u er s

• eziS r ale ted em a us r se b esa d on so em uo pt ut rf om eht soft aw re pro .ssec T sih may be il n se of d le i ev red sour ec co ed , ob tcej c do e

sni tru itc o sn , te .c • Fu itcn on-r ale ted m sae ur se b sa ed on na itse mate of eht fu cn tiona il ty of eht d le ivered so awtf re. Fu cn tion-po stni are eht be ts nk o nw of siht type of me sa ure.

eM asu emer n t p or bl sme

• E its mati gn eht s zi e of ht e me sa ure (e.g. how am ny fu cn tion po ni st ).



• E its mati gn eht to lat numb re of progra mm er mo tn hs taht ha ev e al p es d. • E its mati gn contr tca or product ivi ty (e.g. docum ne t ita on aet )m and cni o pr or gnita th si se t mi a et ni o ev r lla estimate .

eniL s edoc fo

tahW ’s a l eni of oc d ?e • The meas ru e saw if r ts p or op des hw en progra sm w re e typed on cards htiw o en enil per card; • How does siht co rr se op dn to ts at me stne sa ni J ava which can sp na se ev ral l ni es or hw re e ht re e c na be ves re la ts a met e stn on o en

enil ? tahW progr ma s hs ould be oc unted sa p ra t of eht tsys me ?

T sih mod le ssa mu se taht ht ere si a nil ear re ital onship b ewte en sys et m s ezi and volume of od cum ne t ita on .

dorP uct ytivi comp ra si no s

T eh lower level t eh la gn ua eg , eht om re produ evitc eht progra mm er T eh as me fu cn tio ilan ty at k se more c do e to i pm el m tne ni a lower- level langu ga e ht an ni a ih gh-le lev la gn ua eg . T eh more v re bo es t eh progra mm er, eht h ehgi r eht produc ivit ty M sae ur se of p or ud itc vity b sa ed on senil of oc de su gg est ht ta programm re s hw o wr ti e v re bo es oc de are more produ evitc t nah programm re s hw o wr ti e comp tca c do e.

yS s leved met o tnemp emit s

Analy sis D ise gn Cod ni g eT sti gn oD c emu n at t noi

ssA e bm ly code 3 weeks 5 weeks 8 weeks 01 2 weeks iH gh-l ve el language 3 weeks 5 weeks 4 weeks weeks 2 weeks

6 weeks

Size Eff tro Producti iv ty

As bmes ly co ed 05 00 li en s 28 wee sk 7 41 il n se /month iH gh-level l na guage 51 00 li en s 20 wee sk 3 00 il n se /month

Fun stniop noitc

Ba es d on a comb ani tion of program hc ar ca ter si t ci s • txe ernal ni pu st and outpu ;st • u res ni ter ca tio sn ; • txe ernal tni er caf es; • liF es u es d by eht system .



A ew i thg si ssa o taic ed iw th ae ch of eseht and ht e fu itcn on po tni cou tn si co pm u et d by mu itl pl iy ng each r wa count by the iew ght na d su mm gni a ll lav ues.

CPU =∑ (no. of ele me stn of g vi en type) X ( ew i thg ).

T eh fu cn tion po ni t c uo tn si m do if ei d by c mo p ixel ty of t eh pro ej ct FPs nac be u es d to etamitse COL dep ne d gni on the a ev rage numb re of COL per FP for a vig en langu ga e • COL = CVA * nu bm er of fu itcn on po ;stni • CVA si a al ngua eg -depend tne tcaf or var gniy from 200-300 of r a ss e bm le la gn u ega to 2-40 f ro a 4 ;LG FPs si ev ry sub tcej i ev . They dep ne d on eht se t ami tor • Aut mo a cit fu itcn on-po tni count gni si impo iss b el .

Ob tcej p io nts

Obj ce t op stni ( tla ernat vi ely n ma ed app il c ita on po stni ) are an a tl ernat evi fu cn tion-r le ated em asure to func it on p stnio when 4 slG or is m ali r la gn uages ra e u des for d leve opme tn .

Obj ce t op stni are ON T eht as me sa ob ej ct cla ss es. • The numb re of object po stni ni a progr ma si a ew i ethg d est mi ate of • The numb re of es par eta scr snee taht are d si pla ey d; • The numb re of r pe or st taht are p or ud c de by the s tsy em; • The numb re of rp ogram om ud les taht um ts be d ve eloped ot us pp lem tne eht databa es oc d ;e

Ob tcej p io nt es noitamit

Obj ce t op stni are ae sier to se t etami from a sp ice fic ita on than fu cn tion po stni sa they are mis ply co cn erned htiw scr snee , repo str and rp ogram im ng la gn uage modu sel . They can theref ro e b e est mi ated ta a iaf rly ae rly po ni t ni ht e d ve elopme tn pro ssec . tA siht ts ag ,e it si ev ry d fi ficu tl to itse m eta eht nu bm er of lines of code ni a

sys et m.

dorP uct ytivi esti etam s • eR al- it me embedded s sy tems, 40-160 P/COL -mo htn . • S etsy ms progr ma s, 1 05 -400 /COL P-month. • C mo em rc lai app acil tio sn , 2 00 -900 /COL P-month. • In bo j ce t op stni , p or duc ivit ty has been saem ured ewteb en 4 dna 50 ob tcej op /stni om nth dep ne d gni on tool us pport na d d ve elop re ac pab ili ty.


S fo tware E ign nee ir ng 10 SI 51

otcaF r s a nitceff g tcudorp i tiv y

ppA l ci a noit nK o egdelw of eht ap itacilp on d niamo si laitnesse rof effe c it ve mod a ni os ftw era ved e nempol t. sreenignE hw o a rl e yda nu d sre t dna a

eirepxe n ec era niamod l evitcudorp tsom eht eb ot yleki .

ssecorP ilauq ty ehT oleved p tnem ssecorp desu nac evah i s a g tnacifin fe f ce t no ivitcudorp ty. sihT si derevoc ni .82 retpahC

ejorP c is t ze The al r reg a tcejorp , the m ro e ti em iuqer r de for et am noitacinummoc s. sseL emit si av elbalia rof de empolev nt os

vidni laudi ytivitcudorp si .decuder

Te ygolonhc oG od pus port et c nh o gol y hcus C sa ESA ,sloot co noitarugifn oppus rt ,smetsys tnemeganam te c. nac evorpmi .ytivitcudorp

gnikroW I sA id s dessuc ni retpahC ,52 teiu q a gnikrow ne v emnori nt htiw tnemnorivne etavirp krow saera .ytivitcudorp devorpmi ot setubirtnoc

ilauQ t a y n itcudorp d vit y llA m te rics ba es d on vol mu e/u tin mit e are lf awed be ac u es they do

not ta ek qu ila ty tni o ca c uo tn . P or du ivitc ty may ge en rally be cni rea es d a t eht co ts of qu ila ty. tI si not elc ar how

produc ivit t /y qua il ty metrics are re etal d. fI r qe uirem ne ts ar e co sn t tna ly chang gni then an approach ba es d on c uo gnitn lines of code si not m ninae gful sa eht p or gram itse fl is not itats c;

Es mit a oit n cet h seuqin

T eh re si no mis p el yaw to m eka na cca urate itse ma et of t eh e ff ro t required to d leve op a so awtf re tsys me • I tin i la tamitse es are b desa on ani dequate fni orma it on ni a u es r requireme stn de inif tion; • The soft aw re may run on u afn m li iar com up et rs or u es wen

cet hnology; • The peop el in ht e projec t may be unknown .

rP o tcej co ts itse m seta may be fles -fulf nilli g • The se tim eta d nife es eht bud teg na d the p or ud tc si adju dets ot m tee eht b du get.

Chan ig n t g e hc n eigolo s

hC an ig ng et chnol go ies may em an that previous itse mati gn experie cn e do se not rac ry o ev r to wen s metsy s • siD tribu det bo tcej s sy tems rat eh r ht an ma fni rame ys st sme ; • sU e of ew b es r iv c se ; • sU e of E PR or datab sa e- etnec red s sy tem ;s • sU e of o ff -the- hs e fl sof awt re ; • leveD o mp e tn f ro dna htiw reu ;es



• Devel empo n u t sing s rc i itp ng lang gau es ; • Th u e se of C ESA tools and orp gra m genera rot s.


• Alg ro ithmi oc c s t m edo ling. • Expe tr judgment. • tsE ima oit n by anal go y. • P ra kinson s' aL w. • Pricing t o win.


Alg ro ithm ci A m odel based on historical cos t inform ta ion that relates som e software cos t mo del ling metric (usua ll y its size) to the project cost is used. An estimate is m ade

of that metric and the m odel pred ci ts the effort required.

Expert Several experts on the proposed software development techniques and j du gement the applic ta oi n domain are consulted. They e ca h es it mate the project

cos t. These es it mates are compared a dn discu ss ed. The es it ma it on process iterates until an agreed es it m ate i s re ca hed.

Estim ati no by This techni uq e is applicable when other p or jects in the same a pp lica it on na alogy domain have been complete .d The cost of a new project is estimated by

analogy with these completed pr jo ects. yM ers (Myers 1989) gives a very clear description of this approach.

ParkinsonÕs ParkinsonÕsLaw states that work e px ands to fill the it me available. Th e Law cost is determined by available resour sec rather than by objecti ev

assessment. If the software has to be delivered in 12 mon ht s and 5 pe po le are ava li able, the effort re uq ired is estimated to be 60 person- months .

Pricing to win The software cost is estim ta ed to be whatever the cus ot mer has available to spend on the project. The estimated effort depends on the cus tomerÕ s b

icirP n ot g win The pr jo e oc tc sts wh eta v t re he cus mot er has t o spend on it. Adv na at ges: Yo u g t te h oc e n art ct. Disadvan at ges :

hT e pr bo abi til y th t ta h otsuc e em r gets th s e yste h m e ro she wants is small. C d stso o n a to cc ru a let y fer lec t t h row e k re uq i er d.

oT p-d wo n na d b motto -up mitse a it o n

nA y t fo h ppa ese r ao ches may u eb se d top- od wn ro tob tom-up. oT p- od wn

a tratS t th s e yste el m vel an t ssessa d h o e v re a s ll ys met function la ity an d h t wo h si i d s e il v re e t d hrough s bu -systems. B to t mo -u p

a tratS t th e oc m op nen t level an tse d i tam e th e e ff r tro equire d for each component. Ad t d hes e e ff tro s to aer ch a fin la estimate.

D emtrape n o t f C ES , SJBIT Pag 1 e 0 6

udget and not on the softw are functional ity.


oT p- e nwod s noitamit • U lbas e tiw h tuo kn wo l de ge of th s e ys cra met hitect ru e an t d he oc mponents th gim ta h eb t pa o tr f th s e ys met .

• Takes in ca ot c uo n t costs such as in et g ar tion , config ru ation manag eme n a t n d doc mu ne tation. • Can un ered stima t et h oc e s o t f s lo v ni g diff uci l t low-level et chn aci l rp oblems.

ottoB m- pu es amit tion

• U lbas e ehw n th a e r hc i et c erut of th s e yste m is known an d oc mponents i ed n it fi de .

• This ac n a eb n ca c ru ate m te h do if th s e ys met has been ed sig den in de at li . • I am t y unde tser imate th tsoc e s of sys met level vitca ities such as in et g tar ion an od d c emu ntation.

Es mit a oit n tem h do s

aE ch tem h do has s rt engths an d weakne ss es. tsE i tam ion sh uo ld eb ab sed on seve ar l meth do s.

fI th od ese n er to turn approxima let y the s ma e resul t ,t hen y uo hav e ins ffu icien i t fn ro m ta ion av ia al bl m ot e ake an estimate.

oS em tca ion sh uo ld eb at ken ot fin d out m ro e in or ed r ot mak e m ero ac e etaruc stimates.

rP i nic g w ot in i os s m te i t sem he only ppa li ac bl em e thod.

icirP n ot g win This pa p aor ch am y see u m n hte ci al and un- ub sine ss like. H ewo v w ,re hen de at ile i d fn mro ation is l ca king it am y t eb h o e nly app or rp ai te s rt a get y. The pr jo e oc tc s t i a s g deer on th b e asi o s f an o tu l ni e rp oposal an d the ed v le empo n t i oc s n iarts n de by th oc ta st.

ated A li eps de c fi ci ta ion may eb neg ito ated or an evol tu ion ra y appr ao ch use d f s ro y ets m ed vel mpo ent.

glA o tir hmic oc s om t d le in g

C tso i e s sti detam as tam a h me at ci al uf nct oi n of pro tcud , project an d pr co e ss rtta i etub s whos e values e era stimated by proj ce t manage sr : • A = troffE BeziS ´ M ´ • A i a s n ro gan si a oit n- eped nden oc t ns at n ,t B reflects th e id sp or trop ionate eff tro for l ra g orp e j tce s an d M is a multipli re er fle nitc g produ tc , p or ce ss an p d e lpo e rtta ib tu es.

The mos t c mo monly su ed pro ta tcud tri etub for oc s t e ts i tam ion is code size. Mos t m edo ls ra e sim li a t tub r hey us d e i ff re ent values f ro A , B and M.


S fo wt are E ign nee ir ng 10 SI 51 Es mit a rucca noit a yc

The is z o e f a os f rawt e sy ets m can only k eb nown ac ruc a let y when i t is nif ished.

eS v are l f i srotca nfl eu nc t e h f e i an l siz e • Us o e f C TO S a dn com op nents ; • Prog ar m nim g nal guage ; • Dis rt i tub ion of sys met . As the ed vel mpo ent pr co e ss prog er sses then the siz e estim ta e eb c emo s m ro e acc etaru .

Es mit a et trecnu ain yt The OC C OMO om de l

• An empiri ac l dom el ab sed on pr jo e tc ex rep ience. • eW ll- od c mu en det , ‘inde ep nden ’t mode w l hich is on t ti de t a o

ceps ifi c softw era vendor. • L no g hi rots y morf i tin ial ve sr ion publishe i d n 198 1 (COC OMO -8 t )1 rh ough vari i suo n ats ntia oit ns ot COCOMO 2. • COC MO O 2 at kes in a ot cc uo n id t ff e er n t a pp r ao c eh s t o softw ed era vel empo n ,t reuse , te c.



OCOC M O 8 1

Description

W ell-understood applications develope yb d small teams.

More complex project s where team members may have limited experience fo related systems.

Complex projects where the software is part of a strongly coupled complex fo hardware, software, regulations and opera it onal procedures.

COC OMO 2

COCO OM 8 aw 1 s ed vel po e d with the sa s mu ption tha t a wat re fall pr co e w ss ould eb su e a d n t d ha t all os ftw w era ould eb deve pol e d f mor s rc atch.

iS nce i st f ro mu al tion t , h re e hav b e een m na y ch na ges in softw ra e en ig n iree ng tcarp i ec an d COCOMO 2 is ed si ng e d to acco mm do ate id ff e er n pa t p aor ches ot software ed vel mpo ent.

OC C OMO 2 edom l s

COCO OM 2 in oc rp ro a et s a ar nge of sub-m do els tha t rp oduce inc aer sin lg y iated l de sof wt a e er stimates. The sub-m edo ls in COCO OM 2 are: • A lpp ci ta ion com op sition model. Use d when softw ra e is oc mpose d rf e mo xis it ng parts.

• Ea lr y design m do el. sU w de hen re uq i mer ne ts ra e av ia labl ub e t gised n ah s n to ye t sta detr .

• Reuse m edo l. Us t de o com t etup h e e ff o tro f integr ita ng uer sabl oc e m op nents.

• Post- cra hite rutc e m do el. Us o de nc t e h s e y ets m a cr h eti c rut e has eeb n ed signe a d n d mo er inf tamro ion ab uo t th s e yste m is av ia al ble.


Form ula P M = 2.4 (KD SI)1 .0 5 × M P M = 3.0 (KD SI)1 .1 2 × M P M = 3.6 (KD SI)1 .2 0 × M

Project complexity

Simp el

Modera et

Embedded


esU fo C OCO M O 2 ledom s

A pp li oitac n moc posi oit n om d le • Supp stro prot to y nip g pr jo e tc s and proj tce s wh re e th i ere s ex et n is ve reuse. • Ba o des n ts an drad es it m eta s of ed vel epo r pro tcud ivity in applica oit n (objec )t points/month. • Takes CAS E t oo l us e int o a cc ount.

roF mul a i s • MP ( = AN P ´ (1 - %reuse/10 0 ) ) / PROD • i MP s th fe e f tro in rep son-months PAN , is ht e number of applica oit n op in a st n P d ROD is th p e roductivity.

ejbO ct tniop vitcudorp ity s e ecneirepx eV r y l wo L wo Nominal Hi hg yreV high

dna c ibapa lity

ESACI mat dna ytiru eV r y low L wo Nominal Hi hg yreV high bapac i ytil

nom/PON( DORP t )h 4 7 13 25 50

D emtrape n o t f CSE, SJBIT Pag 1 e 1 0

oleveD p Õre


raE l d y e ledom ngis tsE i tam e s can m eb ade afte t r h er e qui er ments have been ag er ed.

Bas o de n ats a ndar d f ro mul a for alg tiro hmi m c odels • MP A = ´ Si ez B ´ M whe er • M EP = R S ´ RC XP ´ RU ES ´ DP IF ´ PREX ´ ICF L ´ SCE ;D • A = 2.9 4 in initial lac ibr oita n , Siz i e n KLOC , B v ra ies f mor 1 1. ot .1 24 eped nding on novelty of the pr jo e ed ,tc vel mpo en t f xel i lib ity ,

risk manage em n t approaches an t d h p e rocess maturity.

Mu itl p sreil Multi lp i fer sre el t tc h c e a bap i til y of th ed e vel repo s, th e non- fun tc ional er quire em nts t , he limaf i ra ity with ht e devel mpo en t lp atf mro , e ct .

• XPCR - rp o cud t er li liba ity an d complex ti y ; • RU ES - th uer e s r e eq riu ed; • DP IF - pl ta form diffi tluc y ; • PR XE - rep sonnel expe neir c ;e • PER S - rep sonnel bapac ility ; • SCED - re uq i er d sche ud le; • F IC L - th aet e m support facil ti ies.

ehT re dom esu e l

• Takes in ca ot c uo nt black- ob x doc e tha t is uer s de with uo t change an d c edo th ta h ot sa be ada tp ed ot in et g etar i t with new code. The t era er wo v re si sno : • Bl ca k-box uer s e whe c er ode is not m do ifi de . An e ff e tro stimate

MP( ) is oc mp tu ed. • White- ob x reus e wh c ere o i ed s m fido ied. A size estima et equivalen t ot t h e n bmu er of lines of new s ecruo code is oc mp etu d. This then da justs the si e ez stimat e f ro new co ed .

Reuse model estimat se 1

F ro gene ar t de c do e: PM = ( SA OL C * A /T 100 /) ATPROD

SA LOC is th e n ebmu r of lines of gen re ate d code TA i t s h rep e ce atn g doc fo e e auto tam i llac y gen tare ed. PTA R DO i t s h orp e d tcu ivity of ne gine re s in integ ar t ni g ht si code.

Reuse om del tse i am t se 2

When doc e h t sa o eb understoo a d n d in et g detar : LSE OC = A LS OC * 1( -AT/100) * AAM.

SA LOC an d AT as bef ero . MAA i t s h da e tatpa ion adjustmen um t ltipl oc rei m up te d rf om the

stsoc of chan ig ng th r e e su e d code t , he costs of und re stan id ng how ot in et g tar e th doc e e an t d h oc e s o st f reuse decision am k ni g.

D emtrape n o t f CSE, SJBIT Pag 1 e 11


ehT xe ponen t t e mr This eped nds on 5 scale fa otc rs (s ee next slide). Thei r s mu /1 00 is adde d to .1 0 1

oc A m ap ny kat es on a pr jo ect in a new amod in. The c eil n t h sa n to ed fine t d h p e roc sse to be use a d n d has n to allowed t mi e f ro risk

an la y is s. Th oc e mpany h a sa C MM level 2 rating. • P er c ede n t n se s - new project 4( ) • Devel empo n t f el xi lib ity - n o lc ei n ni t volve em n t - Very high 1( ) • A hcr i et c r/erut isk tuloser ion - No risk an la y is s - V. . woL (5) • Te ma cohesion - n aet we m - nominal 3( ) • Pr seco s m ruta ity - s emo con ort l - n mo inal 3( )

acS el fa rotc is th re ef ro e .1 71 .

cs tnenopxE ale facto sr

Preceden et end ss eR lf ects the previ uo s pxe re ience of the organis ta ion with th si type of projec t. Very low means no pre iv ou e s xperi ne ce, xE tra high m eans that the organisation is comple et ly familia r with t ih s a pp lication doma ni .

Development eR elf ct s the deg eer of flexib li ity in th e developm ne t process. Very fl xe ibil ti y low e m ans a prescrib de process is use ;d E tx ra high means that the

client only es st general og la s.

A cr hitectu er /r si k eR lf ects the extent of risk a lan isy s carried uo t. Very low m eans il ttle resolution analysis , txE ra hi hg means a complete a thorough risk ana ly is s.

Team c eho is on Ref el cts how well the d ve el po ment team know ea hc other na d work together. Very low me na s very di iff uc lt interactions, Extra high means na ni t ge rated a dn fe fective et am w ti h no communication prob el ms.

Proc se s maturi yt eR lf ects the process maturit y of the organis ta ion . The oc m up ta tion of t ih s av lue ped e dn s on th e C M aM M turity Quest nnoi aire bu t an es it m ta e can be a c hieved by s bu tracting the C M M process matur ti y level from 5.

Mu itl p sreil Produc t a rtt ib setu : Con rec n de w ti h re uq i der ch cara t re istics of th e os f erawt rp oduct eb ing ed vel po ed. oC m rtta retup i setub : i stniartsnoC m o desop n th os e ftw era by th e

h dra w era platf mro . nosreP nel tubirtta es: Multipl t srei h e eht ekat ta x rep ience an d

capabi il ti o se f th p e e po l w e ork ni g on th p e roj ce t i tn o a cc ount. Projec t a rtt i etub s: Concerne d with the rap ti uc la hc r a tcar e ir stics of the softw ra e ed vel mpo en p t roj ce t.

ejorP c t p al n in n g

lA g ro ith im c c m tso od le s provide a ab sis f p ro roje tc plan in ng as they la low alte nr a it v e s etart gies to be compared.



• Em eb dde d s cap e arc f s t ys met Must be reliabl ;e • M tsu im nimize w gie h ( t number of chips ;) • M tlu i lp ie o sr n rel ai lib ity an oc d m tup e r cons rt aints > 1.

tsoC componen st raT g te h awdra r eD;e vel mpo en p t l ta f eD;mro vel po em nt eff ro t

M na a tnemeg op it o sn

M na a tnemeg o itp o n costs

noitpO c ioh c e pO t noi R YLE S ROT TIME TOO SL L XET Total eff tro Soft aw re oc st aH rdw era Tot la co ts

c tso A 93.1 1. 60 1.11 68.0 1 63 93949 3 100000 3939401 B 93.1 1 1 21.1 22.1 88 13135 05 120000 5202041 C 93.1 1 1.11 68.0 1 60 56598 3 105000 3560001 D 93.1 1. 60 1.11 68.0 48.0 51 00967 8 100000 094798 E 93.1 1 1 27.0 22.1 56 24448 5 220000 401 9514 F 93.1 1 1 21.1 48.0 57 81158 0 120000 6072001

O oitp n D (us e mo e er x rep ei nce d s fat f ) appears to be the best al ret n ta iv e • H wo e ,rev i t h a sa h gi h a oss ciat r de isk as ex ep r decnei staff may eb diffi ot tluc find.

oitpO n C ( pu grade mem ro y ) h a sa l wo e r c tso sa niv g tub v re y low risk. Ov lare l t , h m e ode r l ev ae l t s h e i atropm n o ec f sta ff xe rep ien ec in softw ed era vel po em nt.



ejorP c d t ura dna noit st iffa ng A s well as e ff e tro stimation am , nag re s um s e t sti am te th ac e el nda r ti er em q riu e c d om lp e it ng p a rojec t na d when s fat f w li l r eb equi er d. C ela n it rad m ac e n be es it m u deta sing a COCOMO 2 of rmula • TDEV = 3 ´ P( M () .0 33+0.2*(B- .1 0 )1 ) • i MP s th fe e f ro t comp tu ation an d B is th e e x op nen oc t mput de as di dessucs a ob ve ( B i 1 s fo t r h e e a lr y pr toto y nip g m edo l). This oc mp tatu io n rp edi t stc he n mo i lan sch ude le for th p e roj tce .

The time uqer i der is in eped n ed n o t f th e n ebmu r of peopl e w ro king on th p e roject.

tS a iff n er g qu emeri n st atS ff uqer ire d can t’ eb com tup ed by id v ni g th d e eve pol men t ti b em y

the re uq i der sche lud e. Th e n bmu er o f pe lpo e row k ni g on a rp ojec t v ra i ped se en id ng on the phas o e f th p e roject. Th rom e e pe lpo e wh o

row k on th p e rojec t ,t he m ro e to at l e ff tro is us au lly requi der . A v re y par id ub ild-up of pe po l o e ften erroc lates with sch ude le s ppil age eK y op in st

• Th ere i s n s a to i lpm e rel oita n hs i teb p ween the rp i ec ch ra g de for s a y mets an d i d st ve pole men t costs.

• aF c a srot ff e nitc g produc it vity in dulc e in id vi aud l a tp i dut e , d mo ia n expe eir nce t , h d e evel po ment orp j t ,tce h e p or jec t siz ,e tool supp ro t an t d he w ro king envi or nment. • oS f am erawt y be rp ice d t o gain oc a n art c t an d th uf e n tc ion la ity da j tsu e d t t o he rp i ec .

• Di ff e er n hcet t n euqi s of cost esti tam ion sh uo ld be us de when est mi nita g costs. • Th e COCOMO mode at l k p se roj p ,tce ro cud t, rep sonnel an d h dra w rtta era i setub in ot a cc oun t when derp i tc ing e ff r tro equi er d. • Alg ro ithmi tsoc c m edo l s s upp ro t auq nti itat ve tpo i no an la ysis as they la l wo th oc e s st of diff ere n tpo t ions t o eb com rap ed. • Th it e m ot e compl a ete proj tce is not prop ro tional t o the n ebmu r of ep opl e w ro king on th p e roj tce .


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So ftw are Engine ering 10 IS51 - WordPress.com · • Formal transf orm ati on • I ntegr ati on fro m reusable com po nen ts S oci o-Tec hnic al Sy ste ms: • A system is a pu