FUZZY AND SWARM INTELLIGENCE FOR SOFTWARE EFFORT ESTIMATION

Bala Krishna Annepu

Abstract


Software effort estimation depends on prediction of size of the project and parameters. The uncertainty in size can be controlled by using fuzzy logic and the parameters can be tuned by using Particle Swarm Optimization. In this Chapter of the thesis Fuzzy Based PSO technique is applied for Software Effort Estimation. A methodology is developed to estimate effort using Fuzzy Logic and PSO with inertia weight. The formulas that were used to implement these models including Triangular Fuzzy set, PSO with inertia weight and de-fuzzification through weighted average method were outlined along with analysis. The experimentation is done with NASA software data set on the proposed models, and the results are tabulated. The measured efforts of proposed models are compared with available models from literature and finally the performance analysis is done based on parameters such as MARE, VARE and VAF.

Fuzzy logic has rapidly become one of the booming technologies in today’s world for developing convoluted control systems. Fuzzy logic is so efficacious that it can address any such applications perfectly as it resembles human decision making with an ability to generate precise solutions from expurgated or unexpurgated information. It is an interlude in engineering design methods, left vacant by purely mathematical approaches and purely logical approaches in system design. While an alternative approaches require accurate equations to statuette real -world behaviors, fuzzy design can inveigle the ambiguities of real-world human language and logic. It provides both an intuitive method for describing systems in human terms and automates the conversion of those system specifications into effective models


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