最大化从代码检查的实验分析和并发java组件的静态分析中获得的信息

M. A. Wojcicki, P. Strooper
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引用次数: 6

摘要

实证研究的结果局限于特定的背景,难以概括,而且研究本身的执行成本很高。尽管存在这些问题,但软件工程中的实证研究是有效的,对研究人员和实践者都很重要。其有效性的关键在于通过检查现有研究,进行准确的最小样本量的功效分析以及通过复制从以前的研究中获益,可以获得最大限度的信息。在并发Java组件的验证和确认(V&V)环境中,该方法被应用于一个受控实验中,该实验检查了自动静态分析工具和代码检查的组合。尽管研究的规模不大,但这些V&V技术的组合被证明具有成本效益,从而有助于V&V技术评估的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximising the information gained from an experimental analysis of code inspection and static analysis for concurrent java components
The results of empirical studies are limited to particular contexts, difficult to generalise and the studies themselves are expensive to perform. Despite these problems, empirical studies in software engineering 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 existing studies, conducting power analyses for an accurate minimum sample size and benefiting from previous studies through replication. This approach was applied in a controlled experiment examining the combination of automated static analysis tools and code inspection in the context of verification and validation (V&V) of concurrent Java components. The combination of these V&V technologies was shown to be cost-effective despite the size of the study, which thus contributes to research in V&V technology evaluation.
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