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International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.7, No.9, Aug. 2015

Performance of Cost Assessment on Reusable Components for Software Development using Genetic Programming

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Author(s)

T.Tejaswini, J. Sirisha Devi, N. Murali Krishna

Index Terms

COCOMO formulas;cost estimation;genetic programming;magnitude of relative error;reuse of component

Abstract

Reusability is the quality of a piece of software, which enables it to be used again, be it partial, modified or complete. A wide range of modeling techniques have been proposed and applied for software quality predictions. Complexity and size metrics have been used to predict the number of defects in software components. Estimation of cost is important, during the process of software development. There are two main types of cost estimation approaches: algorithmic methods and non-algorithmic methods. In this work, using genetic programming which is a branch of evolutionary algorithms, a new algorithmic method is presented for software development cost estimation, using the implementation of this method; new formulas were obtained for software development cost estimation in which reusability of components is given priority. After evaluation of these formulas, the mean and standard deviation of the magnitude of relative error is better than related algorithmic methods such as COCOMO formulas.

Cite This Paper

T.Tejaswini, J. Sirisha Devi, N. Murali Krishna,"Performance of Cost Assessment on Reusable Components for Software Development using Genetic Programming", International Journal of Information Technology and Computer Science(IJITCS), vol.7, no.9, pp.46-51, 2015. DOI: 10.5815/ijitcs.2015.09.07

Reference

[1]Sonia Manhas, Rajeev Vashisht, and ReetaBhardwaj (2010) “Framework for Evaluating Reusability of Procedure Oriented System using Metrics based Approach”, International Journal of Computer Applications (0975 – 8887), Volume 9– No.10, November 2010. 

[2]L. Hareton and F. Zhang, “Software Cost Estimation “, Polytechnic University, Hong Kong, 2004

[3]D. Hemer, “Specification-based retrieval strategies for component architectures”, Proceedings of the 2005 Australian Software Engineering Conference (ASWEC’05), pp.233-242, 2005.

[4]V. R. Basili, L. C. Briand, and W. L. Melo. A Validation of Component-Oriented Design Metrics as Quality Indicators IEEE Transactions on Software Engineering, 22(10):751– 761, Oct. 1996. 

[5]Ajay Kumar (2012) “measuring software reusability using svm based classifier approach”, International Journal of Information Technology and Knowledge Management January-June 2012, Volume 5, No. 1, pp. 205-209. 

[6]H. Leung and F. Zhang, “ Software Cost Estimation,  Department of Computing”, the Hong Kong Polytechnic University, Hong Kong, 1998

[7]R. Valerdi, “ Pioneers of Parametric”, MIT, Cambridge, USA, 2007

[8]B. Boehm and C. Abts, “ Software Development Cost Estimation Approaches – A Survey”, University of Southern California, Los Angeles, USA, 2002

[9]Cost Estimating Software PRICE Systems, http://www.pricesystems.com

[10]N. Merlo and M. Martin.” COCOMO”, Department of Computer Science, University of Zurich, Switzerland, 2003

[11]F.G. Heetstra, “Software Cost Estimation”, faculty of Public Administration and Public Policy, Twente University, POB 217, Enschede, Netherlands, 1992

[12]SEER –Cost Estimating Software ,http://www.gaseer.com

[13]B.Boehm, C. Abts, B. Clark, S.D.Chulani, E. Horowitz, R. Madachy, D. Refier, R. Selby and B. Stecce, “ COCOMO II Model Definition manual”, 1998

[14]B.Boehm,” COCOMO 2.0: Recent Development”, USC COCOMO/SCM, 1994

[15]Parvinder Singh Sandhu and Hardeep Singh, 2006,“Automatic Reusability Appraisal of Software Components using Neuro-Fuzzy Approach”, International Journal Of Information Technology, vol. 3, no. 3, pp. 209- 214. 

[16]R. Poli, W.B. Langdon and N.F.McPhee, “ A Field Guide to genetic Programming”, University of Essex –UK, university of Minnesota, Morris –USA, 2008

[17]I. Soute, “ Genetic Programming”, 2000

[18]S.D.Lee, Y.J.Yang, E.S.Cho, S.D.Kim, S.Y.Rhew, “COMO: A UML- BasedComponent Development Methodology”, IEEE, 1999.

[19]http://unbox.org/wisp/trunk/cocomo/data/coc81modetypelangtype.csv

[20]http://unbox.org/wisp/trunk/cocomo/data/nasa93.csv

[21]H.K.Kim, Y.K.Chung, “Transforming a Legacy System into Components”, Springer-Verlag Berlin Heidelberg, 2006.

[22]Rajesh K Bhatia, Mayank Dave, R.C Joshi, “Retrieval of most relevant reusable Component using genetic algorithms”, Software Engineering Research and Practice 2006, 151-155.

[23]http://unbox.org/wisp/var/dan/sandbox/cocomost/log/LC.crunch

[24]R. Kazman, S.G.Woods, S.J.Carrii, "Requirements for Integrating Software Architecture and Reengineering Models: CORUM II", IEEE, 1998

[25]Stender (1994) “Introduction to genetic algorithms”, IEEE Colloquium on Genetic Algorithms, Volume 2, March 15, 1994 pp. 1-4. 

[26]Melanie Mitchell (1996) “An Introduction to Genetic Algorithm”, MIT Press, 1996. 

[27]Esteva, J. C. and Reynolds, R. G. (1991) “Identifying Reusable Components using Induction”, International Journal of Software Engineering and Knowledge Engineering, Vol. 1, No. 3 , 1991, pp. 271-292. 

[28]Caldiera, G. and Basili, V. R. (1991) “Identifying and Qualifying Reusable Software Components,” IEEE Computer, February 1991. 

[29]Prof. KulwinderS.Mann and Amanpreet Singh, “A SVM Based Approach For Reusability Evaluation of Object Oriented Based Software Components”, International Journal of Research in Engineering and Technology (IJRET) Vol. 1, No. 3, 2012 ISSN 2277 – 4378.

[30]Brad Clark. "Calibration of COCOMO II.2003", 17th International Forum on COCOMO and Software Cost Modeling, http://sunset.usc.edu/events/2002/cocomo17/Calibration% 20fo%20COCOMO%20II.2003%20Presentation%20-%20Clark.pdf

[31]Brad Clark. COCOMO II Database, CSE Annual Research Review, March 11, 2002

[32]Basili, V.R., Briand, L.C., and Melo, W.L.: A validation of object oriented design metrics as quality indicators. IEEE Trasactions on Software Engineering 22(10)  (1996) 751-761

[33]Khoshgoftaar T. M., Allen, E. B., Kalaichelvan, K. S., and Goel, N.: Early quality prediction: A case study in telecommunications, IEEE Software 13(1) (1996) 65-71.

[34]Khoshgoftaar T. M., Pandya, A.S., and Lanning, D. L.: Application of neural networks for predicting faults,Annals of Software Engineering 1(1) (1995) 141-154