软件可靠性增长模型应用结果中不稳定情况趋势的实证研究

Kiyoshi Honda, H. Washizaki, Y. Fukazawa, Masahiro Taga, Akira Matsuzaki, Takayoshi Suzuki
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引用次数: 3

摘要

监视软件可靠性增长模型(srgm)的结果有助于评估项目的情况。srgm通过分析检测到的bug数量与检测时间之间的关系来预测软件中剩余的bug数量,从而度量软件的可靠性。有时候,SRGM结果会导致管理者做出错误的决策,因为结果是随时间变化的临时快照。在我们之前的研究中,我们提出了一种方法,通过监测SRGM应用的结果来帮助评估项目的质量。我们收集了e-Seikatsu为房地产企业提供的云服务在测试阶段检测到的bug数量和检测时间。数据集包含34个云服务特性。我们的方法提供了29个特征的正确答案和5个特征的错误答案。本文根据结果的趋势,将不稳定特征的监控结果分为四种类型,以帮助开发人员和管理人员对开发状态做出适当的决策。
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Empirical Study on Tendencies for Unstable Situations in Application Results of Software Reliability Growth Model
Monitoring the results of software reliability growth models (SRGMs) helps evaluate a project's situation. SRGMs are used to measure the reliability of software by analyzing the relations between the number of detected bugs and the detection time to predict the number of remaining bugs within the software. Sometimes the SRGM results lead managers to make incorrect decisions because the results are temporary snapshots that change over time. In our previous study, we proposed a method to help evaluate a project's qualities by monitoring the results of SRGM applications. We collected the number of detected bugs and the detection time in the test phases for cloud services provided by e-Seikatsu to real estate businesses. The datasets contain 34 cloud service features. Our method provides correct answers for 29 features and incorrect answers for 5 features. In this paper, we classify the monitoring results of unstable features based on the tendencies of the results into four types to aid developers and managers to make appropriate decisions about the development status.
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Message from the WoSoCer 2018 Workshop Chairs Software Aging and Rejuvenation in the Cloud: A Literature Review Spectrum-Based Fault Localization for Logic-Based Reasoning [Title page iii] Software Reliability Assessment: Modeling and Algorithms
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