過去30年來，專家學者提出了許多軟體可靠度成長模型來預估產品的可靠度。傳統的可靠度模型大多假設偵測到的錯誤可以馬上被移除。實際上，工程師需要分析和找出失效的原因，所以我們不應該忽略錯誤偵測和移除錯誤之間所花費的時間。本篇論文中，我們將會考慮移除錯誤的時間並應用排隊理論來推導新的軟體可靠度成長模型於軟體測試與操作階段。
首先，測試階段之系統較為不穩定，需要投注較多的資源去作錯誤偵測與移除的工作。因此我們使用無限伺服器排隊模型於測試階段。除此之外，錯誤移除的速率會因為某些因素造成變動，所以我們另外將多重動變點應用於無限伺服器排隊模型，同時將此模型與傳統的軟體可靠度作比較。而操作階段的系統較為穩定，除錯所需資源減少，故此階段改採有限伺服器排隊模型。有限伺服器排隊模型可幫助程式開發者預估軟體可靠度並計算所需的開發人員數目。另外，還能計算出每個錯誤平均需要花多少時間才會被移除以及平均會有幾個錯誤存在系統裡。實驗結果顯示，我們所提出的架構比起傳統軟體可靠度有著相當準確的預測能力。

Over the past 30 years, many software reliability growth models (SRGMs) have been proposed for estimation of software reliability growth. One common assumption of conventional SRGMs is that detected faults are removed immediately. In reality, this assumption is unreasonable. Therefore, we should not ignore the fault correction time. In this thesis, we will take the fault correction time into consideration and use a queuing theory in order to model the fault correction process during test and operational phases. In a test phase, a project may be found to be unstable and therefore may need many resources to find and fix the bugs. We propose an infinite server queuing (ISQ) model in order to predict reliability. In addition, the fault correction rate may change at some moments in time which are called change-points (CPs). Thus, we incorporate CPs into the ISQ model. During the operational phase, because the resources are limited and controlled, we use a finite server queuing (FSQ) model. This model can help developers measure the project reliability and thus estimate the number of debuggers needed for the project. We can also estimate the average number of faults in the queue and the system, as well as the response time and waiting time of faults. Experimental results show that the proposed models can predict the behavior of software development more accurately.

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