為了使軟體釋出後確保功能正常，在釋出前之檢測作業極為重要，目的是找出開發過程中產生的程式碼或其他錯誤並修正之，而其中軟體可靠度成長模型能有效地評估軟體的品質與可靠度，其成長概念即是藉由檢測時的偵錯與除錯作業減少軟體內的錯誤並降低失效發生率，使軟體越來越可靠。有關軟體可靠度成長模型的討論已有四十餘年的歷史，然而極大部分依舊是以瞬間除錯與完美除錯的情境下討論，前者表示一偵測到錯誤的瞬間即除錯完畢，後者表示除錯時可將錯誤永遠移除且不會產生新錯誤，但兩者都與實際檢測情況不符。
因此本研究為使軟體可靠度成長模型更能應用於實際檢測環境，我們將移除瞬間除錯與完美除錯的假設，即加入除錯過程與不完美除錯效應於軟體可靠度成長模型中，前者表示已偵測之錯誤需要一段時間除錯才能移除；後者表示在除錯時有機會產生新錯誤，兩者都是符合實際檢測環境的狀況，此外現今多數軟體為延長在市場上的壽命與回應消費者期待，會進行多次更新作業，因此本研究把此模式納入以擴大模型應用範圍。為了驗證本研究之模型適合描述現實檢測情況，我們以各種不同的實際檢測資料集進行配適，並發現都較過往學者之模式為佳。確認模型的表現良好後，本研究進一步建構檢測成本模式，目的是找出最佳檢測時間使檢測成本最小化，並利用兩種求解法得到最佳解，第一種是過往學者最常使用的依序求解法，而為了解決此法不能得到所有版本總合的最佳解以及無法提供決策者停止更新的決策準則，本研究提出第二種方法，即動態規劃法，且發現此法能有效改善依序求解法的缺點，並針對成本函數進行敏感度分析，發現風險成本變動影響最大，此外也發現不完美除錯比例與總錯誤數量的改善可使最小成本改善最多。

Since software testing requires a great amount of testing staff and resources, how to effectively test the software becomes an important issue. Software reliability growth models assist testing teams in evaluating the quality and reliability of the software. The concept of reliability growth is to reduce the software errors and failures by testing and debugging the software, which enhances the reliability of the software. Testing teams can use software reliability growth models to estimate the reliability and testing cost of the software, and then obtain the optimal release time of the software. The software reliability growth models have been studied for more than forty years. However, software reliability growth models are often constructed based on the assumption of instantaneous debugging, which refers to that once an error is detected, it would be removed instantaneously, and perfect debugging, which refers to that errors would be removed eternally, and new errors would not emerge during the debugging process. However, in practice, debugging takes time, and new errors may emerge during the debugging process, which is imperfect debugging. Therefore, instantaneous debugging and perfect debugging are unrealistic. This study proposes a software reliability growth model by removing the assumptions of instantaneous and perfect debugging with consideration of the debugging process, which indicates that once an error is detected, it would be removed after a while, and imperfect debugging effects, which indicates that new errors may emerge during the debugging process, for a practical consideration. In addition, most software are required to perform updates to extend their product life in the market to correspond with consumers’ expectation. This study also incorporates software updates into the software reliability growth model for a practical consideration. Moreover, this study uses data sets to examine the effectiveness of the proposed model to evaluate the fitness of the data sets and find that the proposed model outperforms the previously proposed models. Then, we also investigate the optimal release time of the software with the aim of minimizing the total testing cost under a certain degree of reliability.

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