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Maximising the information gained from a study of static analysis technologies for concurrent software

机译:最大化从并发软件静态分析技术研究中获得的信息

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The results of empirical studies in Software Engineering are limited to particular contexts, difficult to generalise and the studies themselves are expensive to perform. Despite these problems, empirical studies can be made effective and they are important to both researchers and practitioners. The key to their effectiveness lies in the maximisation of the information that can be gained by examining and replicating existing studies and using power analyses for an accurate minimum sample size. This approach was applied in a controlled experiment examining the combination of automated static analysis tools and code inspection in the context of the verification and validation (V&V) of concurrent Java components. The paper presents the results of this controlled experiment and shows that the combination of automated static analysis and code inspection is cost-effective. Throughout the experiment a strategy to maximise the information gained from the experiment was used. As a result, despite the size of the study, conclusive results were obtained, contributing to the research on V&V technology evaluation.
机译:软件工程实证研究的结果仅限于特定情况,难以概括,而且研究本身执行起来很昂贵。尽管存在这些问题,经验研究还是可以有效的进行,对研究人员和从业人员都非常重要。其有效性的关键在于通过检查和复制现有研究并使用功效分析获得准确的最小样本量而获得的信息最大化。该方法被用于受控实验中,该实验在并发Java组件的验证和确认(V&V)的上下文中检查了自动静态分析工具和代码检查的组合。本文介绍了此受控实验的结果,并表明将自动静态分析与代码检查相结合具有成本效益。在整个实验过程中,都采用了最大化从实验中获得的信息的策略。结果,尽管研究规模很大,但仍获得了决定性的结果,为V&V技术评估研究做出了贡献。

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