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Estimating the Accuracy of Dynamic Change-Impact Analysis Using Sensitivity Analysis

机译：使用灵敏度分析估算动态变化影响分析的准确性

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The reliability and security of software are affected by its constant changes. For that reason, developers use change-impact analysis early to identify the potential consequences of changing a program location. Dynamic impact analysis, in particular, identifies potential impacts on concrete, typical executions. However, the accuracy (precision and recall) of dynamic impact analyses for predicting the actual impacts of changes has not been studied. In this paper, we present a novel approach based on sensitivity analysis and execution differencing to estimate, for the first time, the accuracy of dynamic impact analyses. Unlike approaches that only use software repositories, which might not be available or might contain insufficient changes, our approach makes changes to every part of the software to identify actually impacted code and compare it with the predictions of dynamic impact analysis. Using this approach in addition to changes made by other researchers on multiple Java subjects, we estimated the accuracy of the best method-level dynamic impact analysis in the literature. Our results suggest that dynamic impact analysis can be surprisingly inaccurate with an average precision of 47-52% and recall of 56-87%. This study offers insights to developers into the effectiveness of existing dynamic impact analyses and motivates the future development of more accurate analyses.
机译：软件的可靠性和安全性受其不断变化的影响。因此，开发人员尽早使用变更影响分析来确定变更程序位置的潜在后果。动态影响分析尤其可以识别对具体的典型执行的潜在影响。但是，尚未研究动态影响分析用于预测更改的实际影响的准确性（精确度和召回率）。在本文中，我们提出了一种基于敏感性分析和执行差异的新颖方法，首次可以估算动态影响分析的准确性。与仅使用软件存储库（可能不可用或包含的更改不足）的方法不同，我们的方法对软件的每个部分进行更改以识别实际受影响的代码，并将其与动态影响分析的预测进行比较。除了使用其他研究人员在多个Java主题上所做的更改之外，我们还使用这种方法来评估文献中最佳方法级动态影响分析的准确性。我们的结果表明，动态影响分析可能出乎意料地不准确，平均精度为47-52％，召回率为56-87％。这项研究为开发人员提供了有关现有动态影响分析的有效性的见识，并激发了更准确分析的未来发展。

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