Modeling and Analysis of Software Fault Detection and Correction Process by Considering Time Dependency

Singapore Nat. Univ., Singapore
IEEE Transactions on Reliability (Impact Factor: 1.93). 01/2008; 56(4):629 - 642. DOI: 10.1109/TR.2007.909760
Source: IEEE Xplore


Software reliability modeling & estimation plays a critical role in software development, particularly during the software testing stage. Although there are many research papers on this subject, few of them address the realistic time delays between fault detection and fault correction processes. This paper investigates an approach to incorporate the time dependencies between the fault detection, and fault correction processes, focusing on the parameter estimations of the combined model. Maximum likelihood estimates of combined models are derived from an explicit likelihood formula under various time delay assumptions. Various characteristics of the combined model, like the predictive capability, are also analyzed, and compared with the traditional least squares estimation method. Furthermore, we study a direct, useful application of the proposed model & estimation method to the classical optimal release time problem faced by software decision makers. The results illustrate the effect of time delay on the optimal release policy, and the overall software development cost.

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    • ") are the same as the paired model obtained in Wu et al. (2007) for the case of gamma debugging delay. "
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    • "Kapur et al. (2005) analyzed the flexible software reliability growth models for distributed systems. Wu et al. (2007) and Xie et al. (2007) proposed the modeling and analysis of software fault-detection and fault-correction processes. Thirumurugan and Willians (2007) proposed the analysis of testing and operational software reliability in SRGM based on NHPP. "

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    • "The proposed model ะก 2 (i)/M(j)/N is the general one of M(i)/M(j)/N models (Jelinski-Moranda, Musa, Littlewood [1] [2] [3]) in the sense that it enables to analyze the systems with nonexponential distribution of duration of intervals between the error detection moments. In case of exponential distribution of duration of intervals between the error detection moments proposed model shows the same results as M(i)/M(j)/N models. "
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