Genetic Fuzzy Inference Mechanism for Software Product Quality Evaluation System

• Main Authors: Yi-Shiou Lee, 李宜修
• Other Authors: Chang-Shing Lee
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/81860598943663798740

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 96 === At CMMI maturity level 4, Quantitatively Managed, quantitative objectives for process performance and quality should be established by organizations and be used as criteria for managing processes. In order to obtain a quantitative understanding of process performance in support of these quantitative objectives, we propose a genetic fuzzy inference mechanism for software product quality evaluation (GFIM-SPQE), which tries to automatically derive the relationship between a number of quantitative metrics defined by ISO/IEC 9126 and software product quality with Genetic Algorithm and to conclude with a quantitative quality measure by the fuzzy inference mechanism. With our proposed mechanism, the questionnaire survey of customer’s and user’s satisfaction about software product quality commonly used in the literature can be replaced to objectively evaluate software product quality. Simulation shows that the quantitative quality measure generated by the proposed mechanism is able to accurately indicate process performance and software product quality.