International Journal of Scientific & Engineering Research, Volume 2, Issue 11, November-2011 1
ISSN 2229-5518
A Comparative study of COCOMO II and
Putnam models of Software Cost Estimation
T.N.Sharma, Anil Bhardwaj, Anita Sharma
Department of Statistics, University Of Rajasthan, Jaipur
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oftware cost estimation is a prediction of the cost of the resources that will be required to complete all of the work of the software project.
Software has a bad reputation about cost estimation. Large software projects have tended to have a very high frequency of schedule overruns, cost overruns, quality problems, and outright cancellations. Instead of it bad reputation, it is impor- tant to note that some large software projects are finished on time, stay within their budgets, and operate successfully when deployed.
A widely respected survey (CHAOS Reports) of software
projects in industry and government, estimated that, only 29%
of software projects in large enterprises succeeded, 53% were
challenged and 18% failed to deliver in proper cost and budg-
et. The projects that are in trouble have an average budget
overrun of 56%. This represents a serious and chronic risk con- trol problem.
Software cost estimation is a complex activity that requires knowledge of a number of key attributes about the project for which the estimate is being constructed. Creating accurate software cost estimates requires knowledge of lots of parame- ters.
The overall process of developing a cost estimate for software is not different from the process for estimating any other ele- ment of cost. There are, however, aspects of the process that are peculiar to software estimating. Some of the unique as- pects of software estimating are driven by the nature of soft- ware as a product. Other problems are created by the nature of the estimating methodologies. Software cost estimation is a
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T.N.Sharma is undergoing his research work from Department of Statis- tics, University of Rajashthan, Jaipur (India).Mob.:9414248794. Email: tnsharma@rediffmail.com
continuing activity which starts at the proposal stage and con- tinues through the lift time of a project. Continual cost estima- tion is to ensure that the spending is in line with the budget. Cost estimation is one of the most challenging tasks in project management. It is to accurately estimate needed resources and required schedules for software development projects. The software estimation process includes estimating the size of the software product to be produced, estimating the effort re- quired, developing preliminary project schedules, and finally, estimating overall cost of the project.
After years of research, there are many software cost estima- tion methods available including algorithmic methods, esti- mating by analogy, expert judgment method, price to win me- thod, top-down method, and bottom-up method. No one me- thod is necessarily better or worse than the other, in fact, their strengths and weaknesses are often complimentary to each other. To understand their strengths and weaknesses is very important when you want to estimate your projects. Two of the well known software cost estimation methods are dis- cussed below:
The form of this model is:
Technical constant C= size * B1/3 * T4/3
Total Person Months B=1/T4 *(size/C)3
T= Required Development Time in years
Size is estimated in LOC
Where: C is a parameter dependent on the development envi-
ronment and It is determined on the basis of historical data of the past projects.
Rating: C=2,000 (poor), C=8000 (good) C=12,000 (excellent). The Putnam model is very sensitive to the development time: decreasing the development time can greatly increase the per- son-months needed for development.
IJSER © 2011
International Journal of Scientific & Engineering Research, Volume 2, Issue 11, November-2011 2
ISSN 2229-5518
One significant problem with the PUTNAM model is that it is based on knowing, or being able to estimate accurately, the size (in lines of code) of the software to be developed. There is
often great uncertainty in the software size. It may result in the inaccuracy of cost estimation.
For all the scale factors and effort multipliers we have taken average for all the parameters. By calculating the final values which we got are
Both the Post-Architecture and Early Design models use the same functional from to estimate the amount of effort and ca- lendar time it will take to develop a software project. The amount of effort in person-months, PM, is estimated by the formula:
n
PM = A x SizeE x ∏ EM
i=1
5
where E = B + 0.01 x ∑ SFj
j = 1
The amount of calendar time, TDEV, it will take to develop the product is estimated by
TDEVNS = C x (PMNS)F
5
∑ SFj =18.97
j=1
5
E = B + 0.01 x ∑ SFj = 1.097
j = 1
n
∏ EM = 0.184295
i=1
n
PM = A x SizeE x ∏ EM
i=1
5
where E = B + 0.01 x ∑ SFj
j = 1
Applying the values on formula : Here we have
5
where F = D + 0.2 x 0.01 x ∑ SFj
j=1
= D + 0.2 x (E – B)
In COCOMO-II effort is expressed as person month(PM). CO- COMO II treats the number of person-hours per month, PH/PM, as an adjustable factor with a nominal value of 152 hours/PM.
The value of n is 16 for the Post-Architecture model effort
multipliers, Emi, and 6 for the Early Design model, the
number of SFi stands for exponential scale factors.
The values of A, B, C, D, SF1 …, and SF5 for the Early Design model are the same as those for the Post-Architecture model.
CALL MANAGER IN ANDROID
A = 2.94
Size = 2.1
E = 1.097
B = 0.91
∏ EM = 0.184295
PM = 1.225196
Actual time taken for this project is 1.5 Months
As a case study we have taken a project in consideration which was developed for an very US based client. The project takes care calls and SMS details for a client.
After completion of project we calculated the efforts (Person- Month) using COCOMO II and got the actual time taken to develop the project. Total line of code of Android is 2122 i.e.
2.1 KLOC.
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International Journal of Scientific & Engineering Research, Volume 2, Issue 11, November-2011 3
ISSN 2229-5518
T.N.Sharma(2011), Analysis of Software Cost Estimation using COCOMO II, IJSER, June 2011 ( Vol 2, Issue 6).
Vahid Khatibi et. al(2011), Software Cost Estimation Me- thods: A Review, Journal of Emerging Trends in Compu- ting and Information Sciences, Volume 2 No. 1, 2010-11.
By the results we can see that time is very dominating factor in Putnam model. Putnam model is basically based on only two variables which is time and size. It is not considering all other aspects of software development life cycle. Whereas in CO- COMO II we are getting more nearer results because it is con- sidering almost all aspects of SDLC.
Anil Bhardwaj, T.N.Sharma, Anita Bhardwaj(2010), Soft- ware Cost Estimation using COCOMO II, Journal of Ma- thematics and System Sciences, V.6(1) pp.14-22.
Barry Boehm et. al (1998), Software Development Cost
Estimation Approaches – A Survey, IBM Research
T.N.Sharma, Anil Bhardwaj, Jagdish Prasad(2010), On Software Cost Estimation, Advances in Information Theory and Operations Research, pp.329-337, Om Parkash (Ed.)
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