A hybrid algorithm to extract fuzzy measures for software quality assessment

Journal of Uncertain Systems

Volumn 7, Issue 3, 2013, Pages 219-237

  Wang, Xiaojing ^a   Ceberio, Martine ^a   Virani, Shamsnaz ^b   Garcia, Angel ^a   Cummins, Jeremy ^c  

^a UNIVERSITY OF TEXAS AT EL PASO   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

^c YOUNGSTOWN STATE UNIVERSITY   (United States)

Author keywords

Choquet integral; Fuzzy measure; Software quality assessment

Indexed keywords

EID: 84880581419     PISSN: 17528909     EISSN: 17528917     Source Type: Journal    
DOI: None     Document Type: Article

References (37)

1. Alavi, S.H., J. Jassbi, P.J.A. Serra, and R.A. Ribeiro, Defining fuzzy measures: a comparative study with genetic and gradient descent algorithms, Intelligent Engineering Systems and Computational Cybernetics, pp.427-437, 2009.
2. Bansiya, J., and C. Davis, A hierarchical model for object-oriented design quality assessment, IEEE Transactions on Software Engineering, vol.28, no.1, pp.4-17, 2002.
3. Brewerton, P.M., and L.J. Millward, Organizational Research Methods: A Guide for Students and Researchers, Sage Publications, 2001.
4. Ceberio, M., and F. Modave, An interval-valued, 2-additive Choquet integral for multi-criteria decision making, Proceedings of the 10th Conference on Information Processing and Management of Uncertainty in Knowledge- Based Systems, 2004.
5. Combarro, E.F., and P. Miranda, Identification of fuzzy measures from sample data with genetic algorithms, Computers & Operations Research, vol.33, no.10, pp.3046-3066, 2006.
6. Davis, L., Genetic Algorithms and Simulated Annealing, San Francisco, CA, Morgan Kaufmann Publishers Inc., 1987.
7. Etzkorn, L.H., W.E.J. Hughes, and C.G. Davis, Automated reusability quality analysis of OO legacy software, Information & Software Technology, vol.43, no.5, pp.295-308, 2001.
8. Geem, Z.W., J.H. Kim, and G.V. Loganathan, A new heuristic optimization algorithm: harmony search, Simula- tion, vol.76, no.2, pp.60-68, 2001.
9. Grabisch, M., A new algorithm for identifying fuzzy measures and its application to pattern recognition, Proceedings of 4th IEEE International Conference on Fuzzy Systems, vol.1, pp.145-150, 1995.
10. Grabisch, M., The application of fuzzy integrals in multicriteria decision making, European Journal of Operational Research, vol.89, no.3, pp.445-456, 1996.
11. Grabisch, M., I. Kojadinovic, and P. Meyer, A review of methods for capacity Identification in Choquet integral based multi-attribute utility theory applications of the Kappalab R Package, European Journal of Operational Research, vol.186, pp.766-785, 2008.
12. Grabisch, M., H.T. Nguyen, and E.A. Walker, Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference, Kluwer Academic Publishers, Norwell, MA, 1994.
13. Granvilliers, L., and F. Benhamou, RealPaver: an interval solver using constraint satisfaction techniques, ACM Transactions on Mathematical Software, vol.32, no.1, pp.138-156, 2006.
14. Hall, M., E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. Witten, The WEKA data mining software: an update, SIGKDD Explorations, vol.11, no.1, pp.10-18, 2009.
15. Kitchenham, B., S. Peeger, and N. Fenton, Towards a framework for software measurement validation, IEEE Transactions on Software Engineering, vol.21, no.12, pp.929-944, 1995.
16. Lorenz, M., and J. Kidd, Object-oriented Software Metrics: A Practical Guide, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1994,
17. Magoc, T., and V. Kreinovich, How to relate fuzzy and OWA estimates, Proceedings of North American Fuzzy Information Processing Society, 2010.
18. Mendel, J., Computing with words and its relationships with fuzzistics, Information Sciences, vol.177, pp.988-1006, 2007.
19. Mitchell, T.M., Machine Learning, 1st Edition, McGraw-Hill, New York, 1997.
20. Modave, F., M. Ceberio, and V. Kreinovich, Choquet integrals and OWA criteria as a natural (and optimal) next step after linear aggregation: a new general justi_cation, Proceedings of MICAI'2008, pp.741-753, 2008.
21. Modave, F., and P.W. Eklund, A measurement theory perspective for MCDM, Proceedings of the 10th IEEE International Conference on Fuzzy Systems, pp.1068-1071, 2001.
22. Moody, D.L., Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions, Data & Knowledge Engineering, vol.55, no.3, pp.243-276, 2005.
23. Osbeck, J., S. Virani, O. Fuentes, and P. Roden, Investigation of automatic prediction of software quality, Proceedings of North American Fuzzy Information Processing Society, 2011.
24. Paulk, M.C., C.V. Weber, B. Curtis, and M.B. Chrissis, The Capability Maturity Model: Guidelines for Improving the Software Process, Addison-Wesley Pub. Co, 1995,
25. Peeger, S., Software Engineering Theory and Practice, Prentice Hall, 2001,
26. Pham, D., A. Ghanbarzadeha, E. Koc, S. Otri, S. Rahim, and M. Zaidi, The bees algorithm-a novel tool for complex optimization problems, Proceedings of 2nd International Virtual Conference on Intelligent Production Machines and Systems, pp.454-459, 2006.
27. Poli, R., J. Kennedy, and T. Blackwell, Particle swam optimization, Swarm Intelligence, vol.1, no.1, pp.33-57, 2007.
28. Pressman, R., Software Engineering: A Practitioner's Approach, McGraw-Hill, 2005,
29. Sommerville, I., Software Engineering, Addison Wesley Publishing Company, Harlow, England, 2004,
30. Takahagi, E., Usage: fuzzy measure-Choquet integral calculation system (λ fuzzy measure and sensitivity analysis), http://www.isc.senshu-u.ac.jp/~thc0456/Efuzzyweb/mant2/mant2.html.
31. Takahagi, E., A fuzzy measure Identification method by diamond pairwise comparisons and φs transformation, Fuzzy Optimization and Decision Making, vol.7, no.3, pp.219-232, 2008.
32. Virani, S.S., S. Messimer, P. Roden, and L. Etzkorn, Software quality management tool for engineering managers, Proceedings of the Industrial Engineering Research Conference, pp.1401-1406, 2008.
33. Wang, J., and Z. Wang, Using neural networks to determine Sugeno measures by statistics, Neural Networks, vol.10, no.1, pp.183-195, 1997.
34. Wang, W., Z. Wang, and G.J. Klir, Genetic algorithms for determining fuzzy measures from data, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, vol.6, no.2, pp.171-183, 1998.
35. Wang, X., J. Cummins, and M. Ceberio, The Bees algorithm to extract fuzzy measures for sample data, Proceedings of North American Fuzzy Information Processing Society, 2011.
36. Wang, Z., K. Leung, and J. Wang, A genetic algorithm for determing nonadditive set functions in information fusion, Fuzzy Sets and Systems-Special Issue on Fuzzy Measures and Integrals, vol.102, no.3, pp.463-469, 1999.
37. Weiss, J.W., and D. Anderson Jr, CIOs and IT professionals as change agents, risk and stakeholder managers: a field study, Proceedings of the 36th Hawaii International Conference on System Sciences, vol.8, pp.249.3, 2003.