軟體可靠度是軟體品質的重要指標，也是軟體開發團隊做相關決策的重要依據。然而，一般的軟體可靠度成長模型的基本假設之一為完美除錯，但在實務中，可能因為移除一錯誤而產生新的錯誤，或是檢測團隊無法立即移除錯誤的情形發生，即為不完美除錯。此外，在軟體發生的錯誤中，有的錯誤對軟體有重大的影響，發生的機率較小；有的錯誤則較輕微，發生機率較大，因此可將軟體所發生的錯誤做分類。在過往的文獻中，多種類錯誤的不完美除錯模型多假設為獨立、互不影響，然而，錯誤間卻可能會互相影響，即移除一種類錯誤有一定機率導入他種類錯誤，而使的累積總錯誤數及錯誤的變化率有所改變。本研究乃以建構一般化軟體可靠度成長模型以求得最佳軟體上市時間為目的，利用非齊次卜瓦松過程描述依時間變動之累積錯誤偵測數，並且考量多種類錯誤的不完美除錯情形，假設錯誤可以被分為引發重大影響的複雜類錯誤及影響較輕微的簡單類錯誤，且在移除複雜類錯誤時有一定的機率會導入新的簡單類錯誤。並建構一檢測成本函數，找出在軟體服從一要求的可靠度標準下之最佳的軟體上市時間。本研究利用最大概似估計法針對所蒐集之錯誤偵測資料進行參數估計，並檢驗模型對資料的配適程度，更進一步與過往文獻中的模型做比較。最後，建構一實例分析，在考量軟體檢測成本及可接受之軟體可靠度標準之下，求出其建議的最佳軟體上市時間，並進一步對此實例之成本函數進行敏感度分析，探討各參數對決策變數及檢測總成本之影響。

This thesis presents a software reliability models based on a nonhomogeneous Poisson process under failure correlation. The software reliability model allows for two different types of failures: major and minor. Major failures are more difficult to detect and remove and also more expensive to remove. Minor failures are easy to detect and inexpensive to remove. When detect and remove major failure, there is chance to introduce not only major failure but also minor failure in the future, which means the different type of failures are related.
With the software reliability model and the cost model, we can determine the optimal release time for the software. The cost model includes: set up cost, daily cost for software test, the cost of failures removing during test period and the cost of failure removing during warranty period. Minimizing the costs and subject to reliability constraints, we can get the optimal release time of the software. A numerical example is provided to illustrate the above techniques in chapter 4. We also used sensitivity analysis to find out which parameter influence the release time the most.

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