Bayesian and Fuzzy Approach to Assess and Predict the Maintainability of Software: A Comparative Study
Author(s) -
Kawal Jeet,
Renu Dhir
Publication year - 2012
Publication title -
isrn software engineering
Language(s) - English
Resource type - Journals
eISSN - 2090-7680
pISSN - 2090-7672
DOI - 10.5402/2012/202980
Subject(s) - maintainability , computer science , bayesian probability , fuzzy logic , data mining , software , reliability engineering , software quality , fuzzy inference , quality (philosophy) , machine learning , artificial intelligence , adaptive neuro fuzzy inference system , fuzzy control system , software development , engineering , software engineering , philosophy , epistemology , programming language
Quality has always been one of the major issues responsible for the success of software. Maintainability is one of the characteristics of software quality. A large number of techniques were developed for the assess and predication of this characteristic. Most of these techniques do not decompose it to an actual assessment level and thus fail to give a detailed account of the impact of specific criteria. These techniques thus constrain their use as the basis for analysis quantitatively. In this paper, we develop a system based on fuzzy inference approach to assess and predict maintainability in a quantitative manner. This system is an enhancement of Bayesian approach which is using activity-based quality model to deal with maintainability. We also compare the proposed fuzzy technique with an existing Bayesian approach to depict the improvement achieved due to the advantageous accuracy of fuzzy over crisp approach.
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