Implementation of a new Size Estimation Model
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The document introduces a new size estimation model for software projects, comparing it with the COCOMO model and demonstrating its increased accuracy in estimating effort and cost. It details the methodology for measuring the size of new, adapted, and reused modules, emphasizing the importance of accurate size estimation as project size increases. The proposed model offers a comprehensive approach to software maintenance and reuse, resulting in improved estimation accuracy over traditional methods.
![Implementation of a new Size Estimation Model
(IJSRD/Vol. 1/Issue 3/2013/0005)
All rights reserved by www.ijsrd.com
423
delivered. It will result in improving software estimation
accuracy.
VIII. COMPARISION TABLE
Modal New kloc
Adapted
kloc
Reused kloc
Estimated
size
Cocomo 1.34 2.2 1.22 4.72kloc
Our
proposed
model
1.34 2.2 1.22 2.2273 kloc
From above table it is clear that the proposed model
provides more accurate size estimates for maintenance.
IX. CONCLUSION
From our proposed model, it is clear that we consider all
three aspects of maintenance: adapted code, new code, and
reused code while computing the size of the software. On
the other side the COCOMO II model, just takes the KLOC
into consideration. Hence our proposed model gives more
accurate values of effort and schedule estimates. Because
these two depends up on the value of size.
REFERENCES
[1] Abran A., St-Pierre D., Maya M., Desharnais J.M.
(1998), "Full function points for embedded and real-
time software", Proceedings of the UKSMA Fall
Conference, London, UK, 14.
[2] Albrecht A.J. (1979), “Measuring Application
Development Productivity,” Proc. IBM Applications
Development Symp, SHARE-Guide, pp. 83-92.
[3] Albrecht A.J. and Gaffney J. E. (1983) "Software
Function, Source Lines of Code, and Development
Effort Prediction: A Software Science Validation,"
IEEE Transactions on Software Engineering, vol. SE-9,
no. 6, November
[4] Basili V.R., Briand L., Condon S., Kim Y.M., Melo
W.L., Valett J.D. (1996), “Understanding and
predicting the process of software maintenance
releases,” Proceedings of International Conference on
Software Engineering, Berlin, Germany, pp. 464–474.
[5] Boehm B.W. (1981), “Software Engineering
Economics”, Prentice-Hall, Englewood Cliffs, NJ,
1981.
[6] Boehm B.W., Abts C., Chulani S. (2000), “Software
development cost estimation approaches: A survey,”
Annals of Software Engineering 10, pp. 177-205.
[7] De Lucia A., Pompella E., and Stefanucci S. (2005),
“Assessing effort estimation models for corrective
maintenance through empirical studies”, Information
and Software Technology 47, pp. 3–15
[8] IFPUG (1999), "IFPUG Counting Practices Manual -
Release. 4.1," International Function Point Users
Group, Westerville, OH
[9] IFPUG (2004), "IFPUG Counting Practices Manual -
Release. 4.2," International Function Point Users
Group, Princeton Junction, NJ.
[10]Jeffery D.R., Ruhe M., Wieczorek I. (2000), “A
comparative study of cost modeling
[11]techniques using public domain multi-organizational
and company-specific data”, Information and
Software Technology 42 (14) 1009–1016.
[12]Jones T.C. (2008), "Applied Software Measurement:
Global Analysis of Productivity and
[13]Quality", 3rd Ed., McGraw-Hill.
[14]Nguyen V., Deeds-Rubin S., Tan T., Boehm B.W.
(2007), “A SLOC Counting Standard,” The 22nd
International Annual Forum on COCOMO and
Systems/Software Cost Modeling. DOI =
http://csse.usc.edu/csse/TECHRPTS/2007/usc-csse-
2007737/usc-csse-2007-737.pdf
[15]Park R.E. (1992), "Software Size Measurement: A
Framework for Counting Source Statements,"
CMU/SEI-92-TR-11, Sept.
[16]Symons C.R. (1988) "Function Point Analysis:
Difficulties and Improvements," IEEE Transactions on
Software Engineering, vol. 14, no. 1, pp. 2-11
[17]UKSMA (1998) MkII Function Point Analysis
Counting Practices Manual. United Kingdom Software
Metrics Association. Version 1.3.1rs](https://image.slidesharecdn.com/ijsrdv1i3005-140801054941-phpapp01/85/Implementation-of-a-new-Size-Estimation-Model-2-320.jpg)
Implementation of a new Size Estimation Model
- 1. IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 3, 2013 | ISSN (online): 2321-0613 All rights reserved by www.ijsrd.com 422 Implementation of a new Size Estimation Model Aruna Chouhan1 Mohsin Sheikh2 1 MTech Scholar(CSE) 2 Asst. Professor 1, 2 MITM,Indore Abstract— In this paper, we present a comparison between the COCOMO size estimation and a proposed size estimation model. Our experimental results show that the proposed model is providing more accurate size. It will help in accurate effort and cost estimation. Ultimately it will result in increase in overall productivity. Size estimation is a very popular task. We also explain the fundamentals of size estimation. I. INTRODUCTION Software engineering cost (and schedule) models and estimation techniques are used for a number of purposes. These include: Budgeting Tradeoff and risk analysis Project planning and control Software improvement investment analysis II. NEED OF SOFTWARE SIZE & EFFORT ESTIMATION Small Projects are very easy to estimate and accuracy is not very important. But as the size of project increases, required accuracy is not very important. But as the size of project increases, required accuracy is very important which is very hard to estimate. A good estimate should have amount of granularity so it can be explained. Since the effort invested in a project is one of the most important and most analyzed variables. So the prediction of this value while we start the software projects, it helps to plan any forthcoming activities adequately. Estimating the effort with a large value of reliability is a problem which has not been solved yet. III. PROPOSED ESTIMATES COMPUTING THE SIZE OF NEW MODULES The module is newly added to the system, thus its size is simply the KLOC added to the preexisting code. It does not consider the effect of module checking and understanding. It is denoted by KLOC(NEW) ---Eq(A) IV. COMPUTING THE SIZE OF ADOPTED MODULES This size is computed using the size of preexisting modules to be adapted and MA factor. Deleted statements are subtracted from number of lines. It is defined as follows: EKLOC(ADAPTED) = AKLOC * MA ---Eq(B) Where FA = 0.4 * MD + 0.3 * MC + 0.3 * MI MD – % of Modified Design MC – % of modified code MI - % of modified integration and testing MA = (DAA + FA + UM)/100 Where DAA - the degree of Assessment and Assimilation FA – Factor of Adjustment MA – multiplier Adjustment UM – measure of unfamiliarity AKLOC is the KLOC of code adapted. V. VALUES OF DAA INCREMENT DAA Increment Level of Adjustment 0 None 2 Basic module search and documentation 4 Some module Test and Evaluation (T&E), documentation 6 Considerable module T&E, documentation 8 Extensive module T&E, documentation VALUES OF UM UM Increment Level of Unfamiliarity 0.0 Completely familiar. 0.2 Mostly familiar 0.4 Somewhat familiar 0.6 Considerably familiar 0.8 Mostly unfamiliar 1.0 Completely unfamiliar. VI. COMPUTING THE SIZE OF REUSED MODULES These modules are not modified, so MD, MC, UM all are zero. It is defined as follows:- EKLOC (REUSED) = RKLOC * MA Eq(C) Where RKLOC is KLOC of reused modules. MA = (DAA + 0.3 * MI)/100 Finally, EKLOC = KLOC(ADDED) + EKLOC(ADAPTED) + EKLOC(REUSED) VII. IMPLEMENTATION We have proposed a unique method for measuring the size of software reuse & maintenance. This method allows the maintainer to measure the size of both software reuse and maintenance work using the same parameters and formulas. This unique method gives actual size of complete reuse and maintenance work based on source code
- 2. Implementation of a new Size Estimation Model (IJSRD/Vol. 1/Issue 3/2013/0005) All rights reserved by www.ijsrd.com 423 delivered. It will result in improving software estimation accuracy. VIII. COMPARISION TABLE Modal New kloc Adapted kloc Reused kloc Estimated size Cocomo 1.34 2.2 1.22 4.72kloc Our proposed model 1.34 2.2 1.22 2.2273 kloc From above table it is clear that the proposed model provides more accurate size estimates for maintenance. IX. CONCLUSION From our proposed model, it is clear that we consider all three aspects of maintenance: adapted code, new code, and reused code while computing the size of the software. On the other side the COCOMO II model, just takes the KLOC into consideration. Hence our proposed model gives more accurate values of effort and schedule estimates. Because these two depends up on the value of size. REFERENCES [1] Abran A., St-Pierre D., Maya M., Desharnais J.M. (1998), "Full function points for embedded and real- time software", Proceedings of the UKSMA Fall Conference, London, UK, 14. [2] Albrecht A.J. (1979), “Measuring Application Development Productivity,” Proc. IBM Applications Development Symp, SHARE-Guide, pp. 83-92. [3] Albrecht A.J. and Gaffney J. E. (1983) "Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation," IEEE Transactions on Software Engineering, vol. SE-9, no. 6, November [4] Basili V.R., Briand L., Condon S., Kim Y.M., Melo W.L., Valett J.D. (1996), “Understanding and predicting the process of software maintenance releases,” Proceedings of International Conference on Software Engineering, Berlin, Germany, pp. 464–474. [5] Boehm B.W. (1981), “Software Engineering Economics”, Prentice-Hall, Englewood Cliffs, NJ, 1981. [6] Boehm B.W., Abts C., Chulani S. (2000), “Software development cost estimation approaches: A survey,” Annals of Software Engineering 10, pp. 177-205. [7] De Lucia A., Pompella E., and Stefanucci S. (2005), “Assessing effort estimation models for corrective maintenance through empirical studies”, Information and Software Technology 47, pp. 3–15 [8] IFPUG (1999), "IFPUG Counting Practices Manual - Release. 4.1," International Function Point Users Group, Westerville, OH [9] IFPUG (2004), "IFPUG Counting Practices Manual - Release. 4.2," International Function Point Users Group, Princeton Junction, NJ. [10]Jeffery D.R., Ruhe M., Wieczorek I. (2000), “A comparative study of cost modeling [11]techniques using public domain multi-organizational and company-specific data”, Information and Software Technology 42 (14) 1009–1016. [12]Jones T.C. (2008), "Applied Software Measurement: Global Analysis of Productivity and [13]Quality", 3rd Ed., McGraw-Hill. [14]Nguyen V., Deeds-Rubin S., Tan T., Boehm B.W. (2007), “A SLOC Counting Standard,” The 22nd International Annual Forum on COCOMO and Systems/Software Cost Modeling. DOI = http://csse.usc.edu/csse/TECHRPTS/2007/usc-csse- 2007737/usc-csse-2007-737.pdf [15]Park R.E. (1992), "Software Size Measurement: A Framework for Counting Source Statements," CMU/SEI-92-TR-11, Sept. [16]Symons C.R. (1988) "Function Point Analysis: Difficulties and Improvements," IEEE Transactions on Software Engineering, vol. 14, no. 1, pp. 2-11 [17]UKSMA (1998) MkII Function Point Analysis Counting Practices Manual. United Kingdom Software Metrics Association. Version 1.3.1rs