T

CHAPTER 7

RESULTS AND DISCUSSIONS

This chapter summarized the obtained results followed by discussion.

7.1 Obtained Results

his research, exploration is based upon the data gathered from the seven diverse

finished Agile Web based information projects, taken from the computer science

student’s course of major project amid most recent 2 year. Average gathered

information from these Agile Web projects are outlined beneath. It is expected that all the

information of seven distinctive project appeals mulled over is right without any

deviation. For Size computation, we have selected the Agile Web point Analysis. They

are a measure of the extent of web applications along with the activities that construct

them.

Table 7.1: Effort Estimation Results (AgileMOW v/s webMO)

Project ID

Language/ Web Technology Used

Actual Effort Eact [P-M]

Model AgileMOW

Model webMO

AWP Estimated. Effort [Eagm] [p-m]

MRE [%]

Web object

Estimate d Effort [Ewbm] [p-m]

MRE [%]

AP1 JAVA for 7 225 5.23 25.24 154 10.82 54.52 web

AP2 XML 1.9 384 1.20 37.08 202 2.93 54.38 AP3 PERL 21 345 26.76 27.41 266 13.54 35.54 AP4 HTML 11 238 7.65 30.46 201 6.42 41.68 AP5 HTML 11.25 167 15.87 41.06 140 6.69 40.57 AP6 SQL for

Web 13 421 8.60 33.85 255 6.90 46.91

AP7 JAVA for 26.5 268 36.54 37.89 232 45.19 70.51 web

MMRE 33.28 49.15

Using described AGILEM

method, precision of these

illustrated in Table 7.1.

EMOW [Litoriya and Kothari, (2013 B)] Effo

se Web Projects Estimation developed using Agile

Figure 7.1: MRE comparison graph

Figure 7.2: Effort comparison graph

ort Estimation

e methods are

7.2 Discussions

The market fruition forces customers to get included in transient Web projects. Various

Web development organizations worldwide don't utilize formal strategies to gauge effort

for new activities, hence depending on expert-based presumption . Furthermore,

numerous Web organizations don't accumulate any information on past projects, which

can later be utilized to gauge effort for new web ventures, and as a result they are not

mindful of how effort is utilized all through their undertakings and on the off chance that

it could be utilized all the more adequately. This research study discusses about a

parametric model of web cost estimation, we accept can be of profit to Web organizations

to help them enhance their effort estimation rehearses. The suggested and improved

model are especially focused at small Web development organizations. Expert-

based effort estimation speaks to the procedure by which effort for a fresh undertaking

to be created is evaluated by subjective means, and is regularly focused around past

experience from creating or overseeing comparable activities. This is by far the most used

technique for Web effort estimation. Assessments can be proposed by a task supervisor or

by a gathering of individuals blending project managers and developers, normally by

method for a meeting to generate new ideas. In the context of web development, our

experience proposes that pure expert based effort estimates are gotten utilizing different

mechanism.

The results are unswerving and hard to keep up applications that unsuccessful to help,

and cost more and take more time to create than anticipated. By and large, the effort

estimation for a particular scenario is not fit to predict and help dodge these issues. The

results [Litoriya and Kothari (2013,B)] show that the proposed methodology gives an

effective mechanism to measure the extent of software systems, differentiate web

programming frameworks, and estimate development effort ahead of schedule in the web

product life cycle to inside +/ -33 % over a scope of web application. Interestingly, with

other accessible strategy, AGILEMOW utilizes crude recorded data about development

capacity and high granularity data about the web framework to be produced and Agile

group, keeping in mind the end goal to complete such estimations AGILEMOW reduces

the MMRE form 49.15 % to 33.28% which reflects the considerable improvement for

web estimation particularly in context with Agile paradigm. Figure 7.1 and 7.2 reflects

the comparative analysis of MRE and efforts respectively. This technique is

straightforward and exceptionally cited in favor of little or average Web based projects

developed under the agile umbrella.

This dissertation offers results on the significance of the Agile attributes and

model parameters for web project data set developed by undergraduate students of the

computer science discipline. The results are considerable, repeatable and can be

improved by any other researchers. This approach involves identification of crucial Agile

factors (cost drivers) and imparting them in the parametric cost model. Through this

approach, the prediction accuracy of the web based application developed using Agile

methods can be significantly improved while the variance is diminished for the dataset

being analyzed. The approach can perk up the confidence of Agile estimator, demonstrate

the prophetic power of web cost models subsequent to local calibration, and make it

uncomplicated to specialize the models to meticulous situations.

S

CHAPTER 8

SUMMERY AND CONCLUSIONS

8.1 Summery

oftware Engineering is the well defined process which lays the roadmap for

development of software’s within the specified schedule and effort and with the

preferred quality. Software designing is concerned with building programming

concentrated frameworks and items inside the imperatives of time, assets, innovation,

quality, and business contemplations. Presently, software’s are the pouring force behind

the majority of the day to day requirements and service delivery, such as entertainment,

health facilities education, business, transport etc. Each one of these areas update or

maintain technologies that offer quality services to their customers. Nearly all of these

software technologies are expensive, intricate, and entail accurate planning to be

developed reasonably fast. The need for precise prediction of the cost and effort of

software projects are uniformly growing. The capacity to degree ventures faultlessly is a

fundamental component of a software engineering discipline. It entails utmost level of

analyses, hard work and the management of the two. Big scale software planning and

control incorporates the usage of quantitative programming evaluation and estimation

models that are situated in the lead of theory and collected historical project data. With

the perpetually expanding size and unpredictability of software's; software development

has turned out to be a more rowdy process and hence desired to take care of even the

simplest action in the process of software development.

The process launches with assessing the approximate size, required effort and

tentative time required for the maturity of the software and stops with the product and

additional work products constructed in different phases of development. The troubles

being appeared in the software developments is cost overrun, schedule overrun and

quality deprivation. Wrong estimation indubitably results a failure in the development

process. Efficient estimation is essential and important in favor of appropriate project

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planning as well as for process control and is one of the basic and key testing assignments

in the software development process.

The broad estimation process demonstrated in Figure 8.1 remnants impervious while

applied to either conventional software estimation or Web effort estimation.

Nevertheless, in spite of sharing alike estimation processes, Web effort estimation

diverges from traditional software cousin for a number of reasons :

Figure 8.1 : Broad Estimation process [Mendes, (2007)]

Therefore, a standout amongst the hugest points of the software building expertise has

been to create useful and down to earth models that productively clarify the software

progression life-cycle and exactly expect the effort required and timetable of creating a

software venture.

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Taxonomy of Existing cost estimation models

Noteworthy research on software cost estimation models begin in the late 60’s.

Subsequently, more robust cost models were developed, i.e. SEER, ESTIMACS,

COCOMO and COCOMO II etc. The literature reports a vast variety of categorization of

the Software Estimation models/methods and techniques. A detailed sorting of cost

estimation methods by dividing them into 6 sorts i.e. A theory based methods, machine

learning methods, empirical methods, regression methods, composite methods and

expertise based methods are presented by a researcher. A categorization given byy [Singh

et al., (2008)] , includes another class the dynamics based procedures. This additional

class of estimation method stress upon the dynamic characteristics of the software

development effort information. A common grouping of effort estimation is proposed by

[Shepperd et al., (1996)] and [Li et al., (2006)]. They grouped them into algorithmic

methods, analogy based, expert judgment, and machine learning.

[Laird and Brennan, (2006)] supplement the various proposed classification of taxonomy

by including strategies utilizing benchmark information, custom models and proxy

points. Models making utilization of a benchmark data allow associations to many-sided

effort estimation focused around existing data acquired by alternate organizations. A

more generalized classification is published by [Leung and Fan (2002)] and [Attarzadeh

and Owe, (2009)] by isolating them into algorithmic and non algorithmic ones. The

whole characterizations referred to above have a typical set of methods, which wording

may change from characterization to grouping, then again, the meaning keeps up the

same. Principally these models were supposed to address conventional software and

development scenario. Though the majority of these models was shaped at about the

same duration, they all experienced the software crisis of increasing size and complexity,

made it hard for the software project team to forecast the cost, schedule accurately. The

ever active area of software cost estimation proceeded with the interests of analysts and

experts who accomplished something in setting the benchmark of software building cost

model. Further, few categories are particularizations of the more basic classifications, this

chapter concentrates on the association of officially existing strategies into Six significant

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d

classes, including the Web estimation techniques as revealed in figure 8.2, giving a

layout cases of every class.

Model-Based

Learning- Oriented

Software Estimation Techniques

Expertise-Base

Regression- Based

Composite -

Bayesian Web Estimation

Figure 8.2 : Taxonomy of Existing Cost Estimation Models

Over late decades, while market strengths, frameworks prerequisites, usage innovation,

and project team were shifting at a relentlessly expanding rate,

a distinctive program

development approach demonstrated to its favorable circumstances above the

conventional one.

Agile Paradigm

The Agile approach of advancement specifically attends to the issues of quick change. An

overwhelming thought in Agile advancement is that, the players might be more viable in

reacting to change in

the event that it can reduce the expense

of data flow among

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individuals, and decrease the snuck past time between settling on a decision to

considering the results of that decision.

In view of the fact that software specialists are not machines. They exhibit incredible

variety in meeting expectations, styles; inventiveness, consistency tidiness, the Agile

methods have become an admired topic in software development communities, giving

rise to much mystification and argument. The Agile Manifesto was printed in 2001, and

offers a good quality, decisive point for examining the Agile methods and understanding

the foundation on which they were built [Beck, (2001)]. The four Agile menifestoes are

shown in the figure 8.3 below.

Figure 8.3: Manifestoes (Policies) of Agile development

The Agile Alliance characterizes 12 agility principles which flesh out the ideas

articulated in the Manifesto. These 12 principles were documented during the February

2001 summit. They present a much more concrete view of the type of activities that

comprise the various Agile software development method.

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The importance of Human aspect

Promoters of agile software development clearly state their confidence that

Human/People are of greater importance informative software project success instead of

processes or tools. Agile development focuses on the talents and skills of individuals,

molding the process to specific people and teams. The critical tip in this announcement

is that the methodology molds to the necessities of the individuals and the group, not the

other path around. On the off chance that software development team allies are to coerce

the attributes of the progression which is helpful to assemble programming, a set of

different imperative qualities must present amidst the individuals on an agile group and

the group itself.

The Agilest are not only advocates, the people. Human or people have been

within the software industry for decades. The software engineering community believes

that if one compose the team of the right people, and attends to their needs, then

individuals will be capable to succeed no matter what. Some say that disciplined

processes and structured tools can also get in the way of project success. Figure 8.4

illustrates the three interconnected aspect i.e. Human, Process and tools for project’s

success. To make one aspect week or underestimated than the other two would make the

project unstable and eliminating any of these would cause the project to fail.

Human being are considered to be most appreciated resource. Industries that create

intellectual property, people have a superlative role, as observed in figure. Process cannot

imagine and create. Tools cannot apply intelligence. Converting ideas into running

software requires human resource. People envision, people understand, people visualize,

people imagine what they suppose to build, and then people transform that vision into

actuality. Writing sophisticated and quality software cannot be imagined without people.

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r

Human

ool Process

Figure 8.4: Role of Human Aspect in Agile

In 2002, agile ventures made up short of what 2% of general projects and short of what

5% of new application advancement ventures. Today, agile undertakings represent very

nearly 9% of all activities and 29% of new application advancement projects, for a 22%

CAGR. The build in task achievement rates can specifically attach again to undertakings

determined through the agile methodology. The Agile approach is well-liked and admired

by its practitioners and has normally been flourishing when deployed for appropriate

projects. Even though Agile methods commenced with small projects, efforts are being

made to extend the approach to bigger application. As per the p inciples and nature of

Agile approach its applicability is most suited to web based

projects. Web based

applications are relatively small in size and perhaps the most interesting and swiftly

changing field in the era of software engineering.

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The majority of practitioners who follows Agile practices have communicated

apprehension over their powerlessness to exactly gauge expenses belongs to Agile web

project advancement. This worry has gotten to be significantly more basic as expenses

connected with improvement keep on increasing.

WebApps – An Emergent Picture

Web-based software can be expressed as any application software that is coded in a

browser-supported programming language and dependent on a pervasive web browser

to make the execution of application [Coward, (2000)].

Web based applications are the eventually means to take benefit of modern technology to

enhance any organization’s productivity & efficiency. Web based application provide

business professionals a prospect to access their business information from anywhere at

any time across the globe. It also makes easy to save time and money and enhance the

interactivity with their customers and partners. Web based applications generally make

use of an arrangement of client side script such as JavaScript, HTML etc. And

server side script, for instance ASP , PHP etc. to build the application. The appearance

and arrangement of the information is managed by client side script, whereas the server-

side script manages all the complex tasks like storage and retrieval of the information.

Web applications are well-liked owing to the universality of web programs, and the

handiness of utilizing a program as a web client.

The amount of web locales on the worldwide internet was near about 634 millions in

December 2012 [Pingdom, (2013)]. This figure simply confirms an impression about the

tremendousness of information open all through the Web. The Web is continuously used

as the conveyance stage for adequate sorts of uses, fluctuating from on line commerce (e-

commerce) application to backend databases to individual static Web pages. A key

reason behind the attractiveness of web application is the potential to upgrade and sustain

these applications devoid of sharing out and installing supporting software on probably

numerous customer machines. It provides the inbuilt support for cross-platform

companionability. Normal web apps incorporate online retail deals, wikis, webmail,

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online barters, and web portals in addition to numerous different functions. The latest

push for web applications is replacing the conventional web applications; these don't

typically require a server to store the data. For example word processor, it stores reports

on our machine, and doesn't need a server. Web applications are capable of providing the

same usefulness and increase the advantage of operating transversely multiple platforms.

Web Cost Estimation

The field of Web effort estimation is relatively new, particularly the estimation area in

Agile development is very recent, it would not be surprising that research findings in

this field may not have reached an industry widely. A foundation stone of Web based

software project management is sound to cost estimation, which is the procedure all the

way through which an expert, a group of experts, cost model, tool, or a grouping of these,

envisages the cost involved in a given task.

In the context of Web software development, cost estimation, speaks to the

achievement of an expected effort for a fresh web project to be produced. Such an

effort estimate can be gotten by expert opinion and/or the utilization of unequivocal

models, those are explained in chapter 3 of this thesis, constructed from past task

information. The major challenge here is to acquire reasonable effort estimates, that is,

guesstimates that are close in quality to the actual effort it will take to finish the new

extend. Right now, there are various challenges in the matter of why effort assessments

need precision. The communities of software cost estimation presently has not conceded

to how to create effectual estimates for Web based software projects. The inconvenience

is that the attributes of the Web based tasks make it troublesome for estimation team to

adjust and put existing methods and models. In the light of various challenges and

difficulties Web cost estimation becomes very significant particularly for the newer

development strategies.

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Web based software development are undoubtedly not the same as ordinary software

improves and, thusly, involve diversely customized routines for impeccable effort

estimation. In the specific environment of Web based development, these concerns are

likewise fundamental and extremely urgent, realized that Web based tasks have petite

calendars and an exceptionally fluidic extension, researchers and professionals have

anticipated and compared cost estimation procedures for Web based ventures utilizing

Software Company and academic datasets over the last 15 years.

Enhancing the quality of web effort estimation is a prime necessity in numerous web

development firms. A consistent quest is always there for improved models and

instruments to help task administrators in their assessing procedure, in specific for the

Web app market, which is picking up a noteworthy offer of the aggregate IT market.

AGILEMOW : A Regimented approach to Agile-web effort estimation

This thesis discussed the necessity for new measurements and model to fast predict the

size and effort for agile based web development projects. The method called web

estimation using COCOMOII for Agile methods AGILEMOW, attends to a need to

obtain web effort estimation in a restricted period using human oriented cost factor

information. Conversing with other existing techniques, AGILEMOW uses agile

characteristics, crudely recorded data concerning development capability along with high

granularity knowledge about the web framework to be created.

Prescient methods concentrate on the design of a customized plan to do the project.

Conversely, versatile methods concentrate on inspecting the current circumstance and

discovering the best result in every step of performing the task [Azadani and Doost,

(2008)]. The initial step of constructing AGILEMOW (Cost estimation of Agile Web

based software) is focused around a compound web object and various traits (attribute)

approaches.

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The research study carried out in this thesis, focuses on development of effort estimation

model for agile web projects. Creation and use of the model is enlightened in detail. The

model was balanced utilizing the exact information gathered from scholarly developed

seven completed web projects.

Sizing Web: The Agile Web Points (AWP)

AWPs like other aberrant measurements such as FPs, Object Points or Web Objects

which indicates users concerning the comparative extent of an application in the light of

truth that they symbolize dynamic ideas that are used to get the span of the web

framework to be developed. In meticulous, AWPs similar to Web objects signifies system

functionality from the perspective of its web entity predictor (Web entity predictors are

the, visual, aural or text content that comes across as part of the user experience on

websites. It may contain, among other things like text, images, sounds, videos and

animations).

A key topic in the origin of Agile development model is the need to improvingly

comprehend, assess and handle change while Agile software is planned and built. It is a

genuine truth that requirements will definitely undergo change [Fowler, (2005)]. Clients

of web products will alter their opinion, their impression of the part of the product will

change, nature's domain in which the product works will change along these lines will the

engineering with which the software is built.

Without the inclusion of the agility factor while computing precise size metric for agile

web development is iniquitous. Agility factor (AF) for agile web size estimation is

defined, as a gauge metric calculated for each web project for the purpose to determine

the agility of particular or group of web point.

Therefore, agile experts analyzing the web entity data obtained through specification will

get the exact size for a framework; however the development effort might be contrasted

relying upon specific qualities of the agile advancement environment, for example,

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people centric features like the aptitude of the development group, and the accessible

supporting instruments, among others. AWP expects to make things less demanding the

effort estimation transform by giving the expert better devices for adjusting this

methodology. This AWP measuring metric has the point of interest of being quick and

simple to apply, every time the obliged chronicled data is accessible. This makes it

particularly suitable to estimate Web-based projects in agile environment.

AWP Table computes the fairly accurate size size of web based system. The weight

allocated, i.e. Low, medium or high to every classification of AWP means the web

advancement effort of each one, and it is focused around the learning and practice of

the expert agile estimator. The weights may be adjusted by the agile estimator, each time

he accepts it is right.

Agile Web Effort Estimation

The AWP size metric is an approximation of the whole volume of the web project and is

simply the initial step towards creating a model for precisely predict effort of Web

applications developed using agile methods. To precisely estimate agile web project

costs, an AGILEMOW cost model has developed and suggested. It is affirmed, the

suggested model is an adaptation and extension of the COCOMO_II [Boehm et al.,

(2000)] and WEBMO [Reifer, (2000)] model. The0proposed model is created utilizing a

mixture of professional opinion and genuine information from completed academic

projects developed by computer science students of undergraduate studies. It facilitates

the agile team to capture the characteristics of the web application as well as Agile

methods efficiently. AGILEMOW’s algebraic formulation builds on the COCOMO II

model with a far reaching information investigation of web projects and critical

environmental condition are considered to address agile Web estimation issues. Agile

environmental factors can have a major influence over the development efficiency

of the development team.

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bc

TUVWX YXZ L[[\]^ (L) = T _ ̀aYTV (TYf)fe

Vde

Where, A is the constant

P1 is the power factor

CFWAi are each of the Cost Factors of Agile Web development.

AWP is size in KLOC

The 23 cost factors (CFWAi ) consequently effort multipliers of the Suggested

AGILEMOW Architectural model are described in chapter 6, few of them are analogous

to those described in WEBMO [Reifer, (2000)] and remaining all are derived from the

environmental condition of agile strategies. All these twenty three variables are

calculated qualitatively by choosing a rating from a well-defined rating scale. The last

adjustment constant in AGILEMOW corresponds to power factor P1 namely the value of

the exponent of the AWP. The value of this exponent is close to 1.00, and it should not,

one or the other is higher than 1.10 or lower than 0.99. In the AGILEMOW effort

equation the constants and power laws for all of the 3 application domains are directly

taken from WEBMO [Reifer, (2000)].

Experimental analysis and model caliberation

The experimental results prove that the model has good estimation accuracy in terms of

effort and MMRE. The suggested method/model is straightforward and especially proper

for little or medium size web frameworks created by making the utilization of Agile

procedures. The formulation of AGILEMOW is elaborated in chapter 6. Calibration and

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Validation of the metric and detailed model is done in expectancy of developing potential

Agile Web products based upon them. A starting alignment for AGILEMOW by

consolidating expert judgment and real information from 7 finished Agile based

Web projects is performed. The ultimate goal is to provide accurate estimates to the

Agile practitioners who use to develop web based application. Using descriptive

AGILEMOW Effort Estimation method, exactness of these Web Project Estimation

created utilizing Agile methods are captured. The results show that the proposed

methodology gives a productive instrument to measure the extent of software systems,

differentiate web programming frameworks, furthermore evaluate the development effort

early in the product life cycle to inside +/ -33 % over a scope of web application.

8.2 Conclusions

The past works on Software cost (Size, Effort) estimation has concentrated on generating

the cost estimation model for general software development paradigm from the available

data. With the advent of relatively newer web development scenario, considerable

research has carried out (chapter 5). When Fast and flexible Agile methods (chapter 4)

came into the existence and widely adopted by Software practitioners, a tailored version

of existing and established estimation method is highly desirable, that can effectively and

accurately address size and effort estimation issues of Agile web development. In this

exploration, the parametric software cost estimation models (Chapter 2) and the allied

calibration methods have been investigated, particularly for the COCOMO [Boehm et

al., (2000)] and WEBMO [Reifer, (2000)] calibrated approach. It is found that these

models have used some limited parameter/cost driver/cost factors that do not necessarily

holds the characteristics and attributes of Agile methodologies to prove the accuracy of

the model. The best and suitable web cost estimation model is found to be WEBMO

[Reifer, (2000)] with 9 varying cost drivers. The results of this parametric model are less

accurate and shows inconsistency when applied for web application projects developed

using people centric Agile methodologies. The major contributions of this dissertation are

as follows.

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1. This thesis introduces an outline of a mixture of programming, estimation

techniques, giving a sketch of a few prominent estimation models presently

accessible. The literature to date shows that AI based procedures are less

experienced than parametric modeling techniques; however, that majority of

methods is faced with the quick pace of progress in software innovation.

2. The AGILEMOW approach discussed in chapter 6 addresses one of the

significant issues confronted by the Agile web building society; the challenge of

making great and solid estimates utilizing data that is generally inadequate and

deficient. The majority of the contemporary empirical software engineering

cost models is aligned utilizing historical data that do not fit for modern practices

and the environment. The chapter presented the development of the new size

metric AWP based on Web Object. This tailored size metric includes Agility

factor in its formulation so as to effectively measure the Agile web project size.

3. On request to secure quick and solid effort estimations of Web

based information framework improvement projects developed using a

specialized Agile scenario, a web effort estimation model for Agile Software

projects has been presented. Considering different challenges faced by the agilest,

the model is proposed and validated to accommodate most of the characteristics

of Agile methodology, especially people centric attributes. The proposed model

that consists of 23 cost factors that surely influences the development cost is

practically implantable and does not supplant the master estimator, however, it

furnishes Agile development group with a device for accomplishing a more

precise estimation, taking into account relevant information in a shorter time. The

work discussed in this thesis is based on the original WEBMO model proposed by

Reifer.

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4. An all-inclusive framework for calibrating the suggested model employing the

Delphi Expert judgment and Bayesian methodology to create robust web cost

estimation models was exhibited in the thesis. This approach has worked

effectively on numerous models like COCOMO II and its other extensions and is

being employed for AGILEMOW. The framework endows with a legitimately

unswerving and prescribed way of making use of practice based expert

judgment data alongside sample information in the decision making procedure.

5. An efficient, cost estimation model for Agile web development, extension to

COCOMO II and WEBMO has been created. Owing to the absence of historical

data of relevant project to empirically calibrate AGILEMOW, a Delphi decided

a-priori model has been produced and further calibrated using a Bayesian

approach. The model portrayed in chapter 6 can be utilized in its present

condition otherwise can be locally attuned to a specific organization anticipate the

size and required effort of the web based software being developed on.

8.3 Recommendations

The answer for enhancing estimation exactitude for diverse development technologies is

not a high innovation issue. No existing devices, models, or philosophies might be

presented as a powerful influence for the issue that independent from anyone else will

have a huge effect. Few recommendations based on this work are as follows

1. The cost estimation issue changes extensively among software development

strategies that do their estimation under altogether different environment

conditions. The recommendations are specific in nature and must be applied to the

web based software project developed using Agile methods.

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2. Web based projects are entirely different from the conventional software project

types. They require a specialized estimation model or tool for predicting accurate

cost.

3. Agile software development is again different from conventional development

methodology. The most paramount ramifications to organizations working in the

Agile way is that it puts more attention to the characteristics and qualities of

individuals considers in the project. These qualities turn into an essential concern

for the would-be Agile group. Therefore estimators should prominently consider

this “human” factor during estimation of such projects.

4. Agile practitioners and Designers can utilize this new web measuring tool called

Agile Web Point and an effort model which is an adjustment of the WEBMO and

COCOMO II model called AGILEMOW to more effectively estimate the

development effort of Agile Web based software projects to be developed. In view

of research work with in excess of 7 scholar projects, suggested tailored version of

estimation model is particularly helpful for small and medium sized web projects.

8.4 Limitations

Though the model is an extension and elaboration of COCOMO II and WEBMO, most of

the preconditions are same. But due to the fact that it is de-signed specifically for the

projects developed within a flexible and rapid environment, the prerequisite condition or

limitations of this suggested model to be functional are listed below

1. It is explicitly designed for web projects so the project supposed to be estimated must

be a web application.

2. It addresses the estimation issues of Agile development environment, therefore the

development environment of the web project must be any of the Agile approach.

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3. Because of the fact that this is the introductory model and calibrated and tested over

few academic projects, therefore the approximate size and scope must not exceed

medium range for a web application.

4. The qualitative data collected by the development team must be factual.

5. It is not necessary that the historical estimates collected are from the same team. The

different web project may have different team of variable size and attributes.

6. Since the Agile activities and its allied methodologies came into the picture after

2001, therefore the project data must not be older than 10 years.

8.5 Future Research Scope and Extension of Work

1. WEBMO has nine cost drivers and this makes it complex to statistically adjust or

calibrate the model without running into problems of over fitting. Though,

the argument is that WEBMO is a complete web cost estimation model eliciting the

entire web development life-cycle. Now consider our data gathering process, when

we faced many problems with the selection of parameter (cost factors), Develop for

(EORG), giving a strong indication to drop the variable. In actual fact, eradicating

a predictor variable is equivalent to stipulate that variations in this variable,

have no consequence on project effort. When the professional in the field and

the detailed behavioral analyses recommend otherwise, very strong evidence

is needed to drop a predictor. For this reason, further research wants to be done to

resolve this issue either by gathering more data or by accepting if fewer

than twenty three parameters can be sufficient to develop a more cost-conscious

model without giving up its coverage.

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2. Given the restricted data points available, AGILEMOW confirms good expressive

value in modeling the relationship between various cost drivers and required project

effort for agile-based web projects. The variation of sub-factor values within used

dataset is restricted, however, due to the environment of the Agile web development

firm performing the work and the domain of projects it executed. It is inexplicable

whether the model will perfectly describe the estimates outside this limited set. On

further examination, we expect to collect further more data points over a wider

assortment of Agile web projects. This data is supposed to allow us to better

calibrate the model and assess its wider applicability.

3. Any parametric cost model that doesn’t use historical data has faced the problems of

measurement error (errors-in-variables problem). This is a contravention of the

assumption made by the multiple regression approach and the Bayesian approach.

Hence, for the intentions of this dissertation, the supposition has implicitly

been made that the random variation in the responses of the various parameters,

little contrasted with the scope of the parameter. But, there exists enough

literature on research done in other provinces that attempt at minimizing the effects

of measurement error. A study is recommended to comprehend how these problems

can be resolved to enhance the accuracy of the AGILEMOW and other models

would be highly recommended.

4. The A-priori values for the calibration by Bayesian framework is acquired

by sampling experts and researchers in the field of study and receiving their view

on impact of parameters on the measures to be estimated. It would be attention-

grabbing that how the prior information matures and how it is supposed to be

utilized for future calibrations when rationalized sampling data is available.

5. The present proposal of AGILEMOW is limited to compute effort for the entire

web development life cycle. A future research activity may possibly

involve collecting data on effort depleted in various activities and studying the

division of effort by activity.

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6. The dissertation presented improvement in accuracy when the broad development

scenario is Agile and software to be developed is web based. A similar study and

development of customized, cost models according to the varying methods of Agile

paradigm as discussed in chapter 4 would be very interesting.

7. Creation of a dynamic model is desirable that enables critical path analysis and

updating. This type of model could be used to update estimates while more data

become obtainable with the development progress.

8. The current results of AGILEMOW model don’t illustrate any significant

differences in prediction accuracy among small and medium size web projects. It

would be motivated to do an analogous study to see if there is an impact on accuracy if

the size increases from medium to large. Such a study can be made after the

collection of sufficient and quality data.

Software estimation researchers and model developers, continue to face the hindrance of not

existing any universal laws of “Software mathematics ” that delineate quantitative relationships

among the variety of independent variables describing the product and the environmental

aspects of the project. Even though some approximate solutions can be found.