文章基本信息

标题：Estimating the Parameters of Software Reliability Growth Models Using the Grey Wolf Optimization Algorithm
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作者：Alaa F. Sheta ; Amal Abdel-Raouf
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：4
DOI：10.14569/IJACSA.2016.070465
出版社：Science and Information Society (SAI)
摘要：In this age of technology, building quality software is essential to competing in the business market. One of the major principles required for any quality and business software product for value fulfillment is reliability. Estimating software reliability early during the software development life cycle saves time and money as it prevents spending larger sums fixing a defective software product after deployment. The Software Reliability Growth Model (SRGM) can be used to predict the number of failures that may be encountered during the software testing process. In this paper we explore the advantages of the Grey Wolf Optimization (GWO) algorithm in estimating the SRGM’s parameters with the objective of minimizing the difference between the estimated and the actual number of failures of the software system. We evaluated three different software reliability growth models: the Exponential Model (EXPM), the Power Model (POWM) and the Delayed S-Shaped Model (DSSM). In addition, we used three different datasets to conduct an experimental study in order to show the effectiveness of our approach.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Software Reliability; Reliability Growth Models; Grey Wolf Optimizer; Exponential Model; Power Model; Delayed S-Shaped Model