為了提升軟體產業的競爭力，在經濟部工業局的大力推廣之下，國內企業紛紛導入由美國SEI(美國軟體工程學院)所提出的CMMI(能力成熟度整合模式)認證。在CMMI成熟度第四級中，明確的提出需作數量化的管理目標，言明組織專案必須建立品質與流程效益的數量化目標;因此本論文提出一套評估軟體產品品質方法，以ISO/IEC 9126所定義評估軟體品質時所需用到的度量指標(Metric)來做為量化的依據，並利用模糊理論中的推論機制推論出其最終的軟體產品品質。另外為了能客觀的評估軟體品質，我們提出以基因演算法來調整模糊推論機制中的參數，並配合自行模擬的資料，來做為參數調整的依據。透過此評估軟體品質的方式，我們可以取代目前文獻中多數所採用的問卷調查客戶與使用者對於軟體產品品質滿意度的評估方式，在訓練的資料量越大的時候，代表著所訓練出來的參數也越準確，因此可以達到準確預估的目的。

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.

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