PMS System FP Analysis. Step-1: Type of FP Count Development project FP count

PMS System

FP Analysis

Step-1: Type of FP Count

Development project FP count

Step-2: Identification of Application Boundary

Party System PMS NAB

Parliament Members

Father

Spouse

property

Party System

NAB System

PMS System

PMS System– NIC– Member name– Date of birth– Qualification– Experience– No. of times in Parliament

Spouse– Spouse name

– Spouse property

– Spouse income Father

– Father’s name

– Father’s property

– Father’s income

Party System– ID– NIC– Political Party– Date Joined Party– Membership Info– Status

NAB System NAB Case

– ID– NIC– Case ID– Case Description– Start Date– Closing Date– Charges

Property Financial information

– Year– Income– Tax/year– Campaign Expense

Step-3: Identification of ILF’s

ILF RET DET Functional Complexity

Parliament Members

3 15 Low

EIF RET DET Functional Complexity

Party System 1 6 Low

NAB System 3 16 Low

Step-4: Identification of Transaction functions and their complexity

EI FTR DET Functional Complexity

Add Data 1 15 Low

Update Data 1 15 Low

Delete Data 1 15 Low

EO FTR DET Functional Complexity

Property Info 1 4 Low

Member Assessment

2 2 Low

EQ FTR DET Functional Complexity

Member w.r.t. Political Party

2 18 Average

Member Party Info

1 3 Low

List of Charges 1 3 Low

Election Expenses

1 2 Low

Tax Details 1 4 Low

Step-5: Calculate Unadjusted FPFunction

TypeFunctional Complexity

    Complexity Total

Function Types

ILF 1 Low X 7 7  

  0 Average X 10 0  

  0 High X 15 0 7

EIF 2 Low X 5 10  

  0 Average X 7 0  

  0 High X 10 0 10

EI 3 Low X 3 9  

  0 Average X 4 0  

  0 High X 6 0 9

EO 2 Low X 4 8  

  0 Average X 5 0  

  0 High X 7 0 8

EQ 4 Low X 3 12  

  1 Average X 4 4  

  0 High X 6 0 16

UFP         50

Step-6: Calculate Value Adjustment Factor

General System Characteristics Value

Data Communication 1

Distributed Data Processing 0

Performance 

5

Heavily used configuration 

0

Transaction Rate 

4

On-line data entry 

2

End-user efficiency 

5

On-line update 3

Complex Processing 0

Reusability 

0

Installation Ease 2

Operational Ease 5

Multiple sites 

5

Facilitate change 

2

Total Degree of Influence (TDI) 35

Step-7: Calculate adjusted FP

VAF = (TDI x 0.01) + 0.65 VAF = (35 x 0.01) + 0.65 VAF = 1

Adjusted FP = UFP x VAF

50      x 1 = 50

Automated Courier System

FP Analysis

Type of FP Count

Development FP count

Bank

Courier service system

m

Customer

Location

Area

City

Office

1

m

1

Office Personnel

Agent

Admin

Employee

m

11

Order

1

1

Shipment

System Boundary

Customer– C_id,name,SSN,address,email,phone

ORDER– C_id, order_id,payment mode,destination address, expected delivery date

OFFICE PERONNEL– ID, name, SSN, address, office id, email, phone

EMPLOYEE– Hiredate, login, pwd

ADMIN– Authorization level, login, pwd

AGENT– Location

OFFICE– Id, location,type(head/local)

SHIPMENT– Order_id,agent_id,shipment_status

LOCATION– City code, city name

– Area code,area name

Calculation of ILFs and EIFs

ILFs– Customer

• No subgroup– Number of RETs = 1– Number of DETs <20

• 1 RETs, <20 DETs Complexity = Low

– Order• No subgroup

– Number of RETs = 1– Number of DETs <20

• 1 RETs, <20 DETs Complexity = Low

Calculation of ILFs and EIFs….

– Shipment• No subgroup

– Number of RETs = 1– Number of DETs <20

• 1 RETs, <20 DETs Complexity = Low

– Office Personnel• Three subgroups (personnel + agent),

(personnel+admin),(personnel+employee)– Number of RETs = 3– Number of DETs <20

• 3 RETs, <20 DETs Complexity = Low

Calculation of ILFs and EIFs…

– Location• Two sub groups

– Number of RETs = 2– Number of DETs <20

• 2 RETs, <20 DETs Complexity = Low

EIFs– Bank

• Complexity: low

Contribution of ILFs and EIFs

Contribution of ILFs and EIFs ILF

–Low 8 x 7 = 56

–Avg 0 x 10 = 0

–High 0 x 15 = 0

EIF–Low 1 x 5 = 5

–Avg 0 x 7 = 0

–High 0 x 10 = 0

Total = 61

Identification of EI’s, EO’s, EQ’sUse Case Transactio

n TypeFTRs DET

sComplexit

y

Add Customer info EI Customer > 5 Low

Delete Customer info EI Customer > 5 Low

View Customer info EQ Customer <19 Average

Create order EI Customer, order >16 High

Add order EI Customer, order >16 High

View order EO Order <20 Low

Inquire order EQ Order <20 Low

Add employee info EI Personnel <16 Low

Update employee info EI Personnel <16 Low

Delete employee info EI Personnel <16 Low

View employee info EO Personnel <20 Low

Inquire employee info EQ Personnel <20 Low

Identification of EI’s, EO’s, EQ’s…         

Add city,are EI Location, Office <16 Low

Delete EI Location, Office <16 Low

Update EI Location, Office <16 Low

View EO Location, Office <20 Low

Inquire EQ Location, Office <20 Low

View main page EO Customer <16 Low

Place order EI Customer, order, shipment

> 5 High

Payment EI Customer, order, shipment

> 5 High

View payment EO Bank, order <19 Low

View location EO Location <19 Low

View shipment EO Shipment, order >6 Average

Inquire city etc EQ Location, office >6 Average

FTR’s Trans Type complexityDET’sUse case

Contribution of transaction functions EI

Low 8 x 3 = 24Avg 0 x 4 = 0High 4 x 6 = 24

EQLow 6 x 3 = 18Avg 1 x 4 = 4High 0 x 6 = 0

EOLow 3 x 4 = 12Avg 2 x 5 = 10High 0 x 7 = 0

Total = 88

Unadjusted function point count

Total count = 88 + 61 = 149

General System Characteristics

1. Data Communication

2. Distributed Data Processing

3. Performance

4. Heavily used configuration

5. Transaction Rate

6. On-line data entry

7. End-user efficiency

8. On-line update

9. Complex Processing

10. Reusability

11. Installation Ease

12. Operational Ease

13. Multiple sites

14. Facilitate change

•Value Adjustment FactorGeneral System Characteristics•Data CommunicationScore = 1•Distributed Data ProcessingScore = 4, Distributed processing and data transfer are online and in both directions•PerformanceScore = 3, Response time of the system is critical during all business hours•Heavily Used ConfigurationScore = 5, There are special constraints on the application in the distributed components of the system.•Transaction RateScore = 0, there is no peak transaction period. •Online Data EntryScore = 4, as more than 20 percent of transactions are interactive data entry.•End User EfficiencyScore = 2, four of the defined factors are a part of the design, which includes pre-assigned functions keys, Mouse interfaces•Online UpdateScore = 3, nearly all the internal logic files are updated regularly over the Internet and the Intranet.•Complex ProcessingScore = 2, at some points in application logical processing is extensive.•ReusabilityScore = 1, reusable code is used with in the application•Installation EaseScore = 1, there are no special considerations, but a setup will be required for installation.•Operational EaseScore = 2, The application will minimize the use of tape mounts and paper handling.•Multiple SitesScore = 1, User requirements require the consideration of needs of more than one installation site.•Facilitate ChangeScore = 3, flexible query and report facility is provided that can handle complex requests.

Total Degree of Influence – TDICan influence the FP count by ± 35%

Value Adjustment Factor – VAF

VAF = (TDI * 0.01) + 0.65

Adjusted FP Count – AFP

AFP = UFP * VAF