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An Empirical analysis of Open Source Software Defects data through Software Reliability Growth Models

机译:通过软件可靠性增长模型对开源软件缺陷数据进行的实证分析

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摘要

The purpose of this study is to analyze the reliability growth of Open Source Software (OSS) using Software Reliability Growth Models (SRGM). This study uses defects data of twenty five different releases of five OSS projects. For each release of the selected projects two types of datasets have been created; datasets developed with respect to defect creation date (created date DS) and datasets developed with respect to defect updated date (updated date DS). These defects datasets are modelled by eight SRGMs; Musa Okumoto, Inflection S-Shaped, Goel Okumoto, Delayed S-Shaped, Logistic, Gompertz, Yamada Exponential, and Generalized Goel Model. These models are chosen due to their widespread use in the literature. The SRGMs are fitted to both types of defects datasets of each project and the their fitting and prediction capabilities are analysed in order to study the OSS reliability growth with respect to defects creation and defects updating time because defect analysis can be used as a constructive reliability predictor. Results show that SRGMs fitting capabilities and prediction qualities directly increase when defects creation date is used for developing OSS defect datasets to characterize the reliability growth of OSS. Hence OSS reliability growth can be characterized with SRGM in a better way if the defect creation date is taken instead of defects updating (fixing) date while developing OSS defects datasets in their reliability modelling
机译:本研究的目的是使用软件可靠性增长模型(SRGM)分析开源软件(OSS)的可靠性增长。这项研究使用了五个OSS项目的二十五个不同版本的缺陷数据。对于所选项目的每个版本,都创建了两种类型的数据集;关于缺陷创建日期(创建日期DS)开发的数据集和关于缺陷更新日期(更新日期DS)开发的数据集。这些缺陷数据集由八个SRGM建模。奥本武藏(Musa Okumoto),拐点S形,奥本Goel,延迟S形,Logistic,Gompertz,Yamada指数和广义Goel模型。选择这些模型是由于它们在文献中的广泛使用。 SRGM适合每个项目的两种类型的缺陷数据集,并分析了它们的拟合和预测能力,以便研究OSS在缺陷创建和缺陷更新时间方面的可靠性增长,因为缺陷分析可以用作建设性的可靠性预测器。结果表明,当使用缺陷创建日期来开发OSS缺陷数据集来表征OSS的可靠性增长时,SRGM的拟合能力和预测质量会直接提高。因此,如果在可靠性模型中开发OSS缺陷数据集时采用缺陷创建日期而不是缺陷更新(修复)日期,则可以用SRGM更好地描述OSS可靠性增长。

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