Why Statically Estimate Code Coverage is So Hard? A Report of Lessons Learned

M. Aniche, G. Oliva, M. Gerosa
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Abstract

The calculation of test coverage is often unfeasible for large-scale mining software repositories studies, as its computation requires building each project and executing their test suites. Because of that, we have been working on heuristics to calculate code coverage based on static code analysis. However, our results have been disappointing so far. In this paper, we present our approach to the problem and an evaluation involving 18 open source projects (around 2,700 classes) from the Apache Software Foundation. Results show that our approach provides acceptable results for only 50% of all classes. We believe researchers can learn from our mistakes and possibly derive a better approach. We advise researchers who need to use code coverage in their studies to select projects with a well-defined build system, such as Maven.
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为什么静态估计代码覆盖率如此困难?经验教训报告
对于大规模的挖掘软件存储库研究来说,测试覆盖率的计算通常是不可行的,因为它的计算需要构建每个项目并执行它们的测试套件。正因为如此,我们一直在研究基于静态代码分析计算代码覆盖率的启发式方法。然而,到目前为止,我们的结果令人失望。在本文中,我们提出了解决这个问题的方法,并对Apache软件基金会的18个开源项目(大约2700个类)进行了评估。结果表明,我们的方法仅对所有类别的50%提供了可接受的结果。我们相信研究人员可以从我们的错误中吸取教训,并可能得出更好的方法。我们建议在研究中需要使用代码覆盖的研究人员选择具有良好定义的构建系统的项目,例如Maven。
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