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外文期刊>Journal of the Chinese Institute of Industrial Engineers
>Better prediction of software failure times using order statistics Nasser Abosaq* (*: abosaq@yic.edu.sa) View all notes Department of Electrical and Electronics Engineering Technology, Yanbu Industrial College, Saudi Arabia Walter Bond Department of Computer Sciences, Florida Institute of Technology, 150 W. University Blvd. Melbourne, FL 32901, USA
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Better prediction of software failure times using order statistics Nasser Abosaq* (*: abosaq@yic.edu.sa) View all notes Department of Electrical and Electronics Engineering Technology, Yanbu Industrial College, Saudi Arabia Walter Bond Department of Computer Sciences, Florida Institute of Technology, 150 W. University Blvd. Melbourne, FL 32901, USA
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机译：使用订单统计信息更好地预测软件故障时间Nasser Abosaq *（*：abosaq@yic.edu.sa）查看所有注释沙特阿拉伯盐步工业学院电气与电子工程技术系Walter Bond佛罗里达学院计算机科学系科技，150 W. UniversityBlvd。美国佛罗里达州墨尔本市32901
The use of software reliability models as an aid in making software release decisions is a well-established practice in software reliability engineering. If the chosen model overestimates the mean time to the next failure (MTTF) or, inversely, underestimates the current defect density, then the software could be released prematurely. A factor that could bring about such an overestimate is a poorly constructed test case suite. If, during testing, one or more suites of test cases take much longer than expected to discover the next defect, the estimated defect density and MTTF can be strongly biased toward the unwarranted early release of the software. This research addresses this problem by considering as outliers the time between failures resulting from ineffective test suites. Using an approach based on order statistics, a bound is constructed such that the probability that the kth largest values (relative to their positions in the ordered series) in the dataset will exceed that bound is (1 â α) for, say, an α of 0.05. This article discusses the development of the order-statistics approach and validates the method by the use of simulations of failure time data which have been randomly contaminated with uncharacteristically large failure times. Additionally, we demonstrate the use of the approach as applied to a number of datasets supplied by the Data & Analysis Center for Software (DACS). (MTTF) K()(1 - α)α0.05 View full textDownload full textKeywordssoftware reliability, software reliability modeling, Jelinski-Moranda model, order statisticsKeywords : Jelinski-Moranda Related var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/10170660903509580
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