Maintainability assessment for software by using a hybrid fuzzy multi-criteria analysis approach

Abstract: Maintainability plays a fundamental role for achieving success in software system and it is con-sidered as an important quality characteristics. Maintainability may be predicted efficiently by us-ing soft computing techniques as they provide good results. In this paper similarity- based ap-proach is used with the contribution of fuzzy Analytical Hierarchical Process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) at 2-level hierarchy. Here similarity- based approach illustrates the combine approach of fuzzy AHP and fuzzy TOPSIS. This approach is used to provide the rank of software to select the best one for maintainability estimation. Also, several factors are presented that influence the software maintainability. These factors are taken as criterion and three software products are taken as alternatives.

How to cite this paper

 Kundu, S & Tyagi, K. (2017). Maintainability assessment for software by using a hybrid fuzzy multi-criteria analysis approach.Management Science Letters , 7(6), 255-274.

Refrences

Cai, L., Liu, Z., Zhang, J., Tong, W., & Yang, G. (2010, August). Evaluating Software Maintainabil-ity Using Fuzzy Entropy Theory. In Computer and Information Science (ICIS), 2010 IEEE/ACIS 9th International Conference on (pp. 737-742). IEEE.
Chen, J., & Liu, X. (2009, December). Software maintainability metrics based on the index system and fuzzy method. In Information Science and Engineering (ICISE), 2009 1st International Con-ference on (pp. 5117-5120). IEEE.
Chidamber, S. R., & Kemerer, C. F. (1991). Towards a metrics suite for object oriented design. ACM, 26(11), 197-211.
Chidamber, S. R., & Kemerer, C. F. (1994). A metrics suite for object oriented design. IEEE Transac-tions on Software Engineering, 20(6), 476-493.
Deng, H. (1999, August). Multicriteria analysis with fuzzy pairwise comparison. In Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE'99. 1999 IEEE International (Vol. 2, pp. 726-731). IEEE.
Deng, H. (2007, August). A similarity-based approach to ranking multicriteria alternatives. In International Conference on Intelligent Computing (pp. 253-262). Springer Berlin Heidelberg.
Dubey, S. K., & Rana, A. (2012). A Fuzzy Approach for Evaluation of Maintainability of Object Ori-ented Software System. International Journal of Computer Applications, 49(21).
Fulei, W. (2010). The research on college teacher performance evaluation based on fuzzy-AHP meth-od. In: Proceedings of the 2nd international workshop on education technology and computer sci-ence, IEEE computer society.
Gani, A. N., & Assarudeen, S. M. (2012). A new operation on triangular fuzzy number for solving fuzzy linear programming problem. Applied Mathematical Sciences, 6(11), 525-532.
Ghosh, S., & Dubey, S. K. (2012). Fuzzy Maintainability Model for Object Oriented Software Sys-tem.
Goel, N., Dubey, S. K., & Rana, A. (2012). Fuzzy layered approach for maintainability evaluation of object oriented software system. International Journal of Scientific & Engineering Research, 3(6), 1.
Gyimothy, T., Ferenc, R., & Siket, I. (2005). Empirical validation of object-oriented metrics on open source software for fault prediction. IEEE Transactions on Software engineering, 31(10), 897-910.
Hwang, C.L., & Yoon, K.P. (1981). Multiple attributes decision making methods and applications. Springer, Berlin, pp 12–21
Jeet, K., & Dhir, R. (2012). Bayesian and fuzzy approach to assess and predict the maintainability of software: A comparative study. ISRN Software Engineering, 2012.
Kumar, V., Sharma, A., Kumar, R., & Grover, P. S. (2012). Quality aspects for component‐based sys-tems: A metrics based approach. Software: Practice and Experience, 42(12), 1531-1548.
Li, W. (1998). Another metric suite for object-oriented programming. Journal of Systems and Soft-ware, 44(2), 155-162.
Mahmood, Z. (1982). Multiple criteria decision making. McGraw-Hill, New York
Momeni, H., & Zahedian, S. (2014). Aspect-oriented software maintainability assessment using Adaptive Neuro Fuzzy Inference System (ANFIS).
Moradi, M., & Ebrahimi, E. (2014). Applying Fuzzy AHP and Similarity-Based Approach for Eco-nomic Evaluating Companies Based on Corporate Governance Measures. Global Journal of Man-agement Studies and Researches, 1(1), 10-20.
Seetha lakshmi V (2013) Decision making in academic institutions: A fuzzy ahp approach. Interna-tional Journal of Engineering Science and Technology, 1(5), 403-409.
Saaty, T.L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
Zhang, L. (2010). Comparison of classical analytic hierarchy process (AHP) approach and fuzzy AHP approach in multiple-criteria decision making for commercial vehicle information systems and net-works (CVISN) project.