Modeling and Analysis of Software Fault Detection and Correction Process by Considering Time Dependency
ABSTRACT 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. "
ABSTRACT: This paper studies the fault detection process (FDP) and fault correction process (FCP) with the incorporation of testing effort function and imperfect debugging. In order to ensure high reliability, it is essential for software to undergo a testing phase, during which faults can be detected and corrected by debuggers. The testing resource allocation during this phase, which is usually depicted by the testing effort function, considerably influences not only the fault detection rate but also the time to correct a detected fault. In addition, testing is usually far from perfect such that new faults may be introduced. In this paper, we first show how to incorporate testing effort function and fault introduction into FDP and then develop FCP as delayed FDP with a correction effort. Various specific paired FDP and FCP models are obtained based on different assumptions of fault introduction and correction effort. An illustrative example is presented. The optimal release policy under different criteria is also discussed.Reliability Engineering [?] System Safety 01/2014; 126. DOI:10.1016/j.ress.2014.01.004 · 2.05 Impact Factor
International Conference on Advances in Modelling, Optimization and Computing (AMOC), IIT Roorkee, 5-7 Dec., 2011; 12/2011
- "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 С 2 (i)/M(j)/N is the general one of M(i)/M(j)/N models (Jelinski-Moranda, Musa, Littlewood   ) 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. "
ABSTRACT: The generalized software reliability model on the basis of nonstationary Markovian system of service is proposed. Approximation by distribution of Cox allows investigating growth of software reliability for any kinds of distribution of time between the moments of detection of errors and exponential distributions of time of their correction. The model allows receiving the forecast of important characteristics: the number of the corrected and not corrected errors, required time of debugging, etc. The diagram of transitions between states of the generalized model and system of the differential equations are presented. The example of calculation with use of the offered model is considered, research of influence of variation coefficient of Cox distribution of duration of intervals between the error detection moments on values of look-ahead characteristics is executed.Proceedings of the 34th Annual IEEE International Computer Software and Applications Conference, COMPSAC 2010, Seoul, Korea, 19-23 July 2010; 01/2010