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Variable Granularity for Improving Precision of Impact Analysis

机译:可变粒度,用于提高影响分析的精度

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Impact analysis is a specialized process of program comprehension that investigates the nature and extent of a planned software change. Traditionally, impact analysis involves inspecting dependencies among the software components of a fixed granularity; these components constitute a dependency graph. In this paper, we argue that a single granularity is insufficient and leads to imprecise analysis. We explain how the precision can be improved by variable granularity, where the programmers choose among the granularity of classes, the granularity of class members, and the granularity of code fragments. We assess the resulting precision in a case study on open-source software.
机译:影响分析是调查计划软件变化的性质和程度的计划理解的专业过程。传统上,影响分析涉及检查固定粒度的软件组件之间的依赖关系;这些组件构成了依赖图。在本文中,我们认为单个粒度不足并且导致不精确的分析。我们解释了通过可变粒度可以改善精度,程序员在类别的粒度,类成员的粒度和代码片段的粒度中选择的。在开源软件的案例研究中,我们评估了结果的精确度。

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