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DIAS Technology Review

The Institute has a unique distinction of publishing a bi-annual International journal DIAS Technology Review – The International Journal for Business and IT. The Editorial Board comprises of...

P-ISSN: 0972-9658 English Since 2004
Current Issue

Vol. 2 No. 2 (2006)

Articles 4th Edition of DTR Oct 2005 – Mar 2006
DOI 10.65301/dias.2005.2.2.395

A Fuzzy Approach for Integrated Measure of Object Oriented Software Complexity

Authors
68 Views
101 Downloads
Published 2005-04-30
Pages 50-55
Abstract

Many methods can be used to measure the complexity of a Object Oriented software, but none o f them takes care of all the characteristics o f the software. Various metrics used in measurement o f OO software complexity are Weighted Methods per Class (WMC), Response for a Class (RFC), Lack of Cohesion of Methods (LCOM), Coupling Between Objects (CBO), Depth Inheritance Tree (DIT) and Number of Children (NOC), but none o f them is alone sufficient to give an overall reflection of software complexity. Different metrics try to measure different characteristics o f the software such as efficiency, complexity, understandability, reusability, testability and maintainability. Depending upon the characteristics o f the software to be measured a subset o f thkse metrics should be used.
This paper proposes a fuzzy model for complexity measurement that integrates the effect of subset o f these metrics i.e. WMC, RFC, CBO and DIT. The paper is about an approach to combine OO software metric values into a single overall value that can be
used to rank classes according to their' complexity. The approach uses fuzzy techniques and concepts, vizfuzzification of crisp metric values, inference and aggregation, defuzzification of fuzzy output etc. 

Keywords
Complexity, Probability of Failure, Object Oriented
References
  1. [1] B. Beizer (1990), Software Testing Techniques. Van Nostrand Reinhold, New York.
  2. [2] C. Ghezzi, M. Jazayeri, and D. Mandrioli (1991), Fundamentals of Software Engineering. Prentice Hall, Upper Saddle River, NJ 07458,1st edition.
  3. [3] Chidamber and Kemerer, (1994), "A Metrics Suite fo r Object-Oriented Design”, IEEE Transactions on Software Engineering, Vol. 20, No. 6, June, pp. 476 - 493.
  4. [4] Chidamber S.R. & Kemerer, C.F. (1991), “Towards a Metrics Suite for Object Oriented Design ’Troc. OOPSLA.
  5. [5] D.D. Banker, S.M. Datar, D. Zweig (1989), “Software Complexity and Maintainability”, Proceedings of Tenth Internationa] Conference on Information Systems, Boston, Dec4-6,p247-255.
  6. [6] Edward V. Berard. Metrics for Object-Oriented Software Engineering, The Object Agency, Inc.
  7. 17] George J. Klir, Bo Yuan (1995), Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall of India, NewDelhi.
  8. [8] Hellendom, C. Thomas (1995), “On Quality Defuzzification: Theory and Application Example”, Fuzzy Logic and
  9. Applications to Engineering, Information Sciences and Intelligent Systems Edited by Z. Bien, K.K. Min, Kluwer
  10. Academic Publication, pp 167-176.
  11. [9] J A McCall, P K Richards, G.F Walters (1977), “Factors in Software Quality”, vol 1 -III, US Rome Air Development Center
  12. Reports NTISAD/A-049014,015,055,NationalTechnical Information Service, US Department of Commerce.
  13. [10] J. Patyra, D. M. Mlynek (Editors) (1996), Fuzzy Logic: Implementation and Applications, lohn Viley & Sons Ltd. And B.G.
  14. Teubner.
  15. [11] K.K. Aggarwal, Yogesh Singh, Jitender Kumar Chhabra (2002), “An Integrated Measure of Of Software Maintainability”, Proceedings of Annual Reliability and Maintainability Symposium- International Symposium on Product Quality and
  16. Integrity RAMS- 2002,SeatleWestinU.S.A, Jan28-31, p.235-241.
  17. [12] K.K. Aggarwal, Yogesh Singh, Jitender Kumar Chhabra (2002), “Towards Com plexity M easurem ent o f Object Oriented
  18. Software”, All India Seminar on Challenges Ahead with Information Technology CAIT-2002, SLIET, Long owal, Jan 19-20, p-90-92.
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