SHF: Small: Partitioning Static and Dynamic Dependences Across Versions

程序员通常会为了修复错误或添加新功能而修改程序。虽然他们通常对他们对程序进行的实际更改有很强的了解，但这些更改对程序运行时行为的动态影响可能更难理解。该方法帮助开发人员确定他们对源代码的更改与后续可执行行为中的更改何时不一致：也就是说，源代码中的更改在行为中不明显，反之亦然。该方法确定了可能导致变更的不一致性质的特定程序元素和依赖项。使用来自两个程序版本中的每一个的静态和动态依赖图，根据它们在四个图中的每一个中的存在或不存在来划分依赖项。特定分区包含可能表示更改的不一致部分的依赖关系；这些分区提供了对否则难以获得的更改的洞察。分区允许仅使用静态依赖图、仅使用动态依赖图进行区分，也不能使用给定版本的静态和动态图对来进行区分；该方法的大部分威力是因为依赖图中的跨版本变化很小，从而减少了提供给程序员的信息。智力价值包括对一系列广泛的计划和变化的经验评估，价值主张？为了使用该信息，该方法的应用，以及使用分区来增强评估软件复杂性的传统方法。该项目涉及两类更广泛的影响：直接参与研究的人，以及研究通过提高程序员生产率积极影响社会的潜力。

Programmers usually modify a program intending to fix a bug or to add a new feature. While they often have a strong understanding of the actual changes they are making to a program, the dynamic effects of these changes on the run-time behavior of the program can be harder to comprehend. The approach helps developers identify when their changes to the source code and the changes in the consequent executable behavior are inconsistent: that is, the change in the source is not apparent in the behavior, or vice versa. The approach identifies specific program elements and dependencies that likely account for the inconsistent nature of the change. Using a static and a dynamic dependence graph from each of two program versions, the dependences are partitioned according to their presence or absence in each of the four graphs. Particular partitions contain dependencies that are likely to represent inconsistent parts of a change; these partitions provide insight into the change that would be otherwise difficult to obtain.The partitions allow distinctions to be made that cannot be made using the static dependence graphs alone, the dynamic dependence graphs alone, nor using a static and dynamic graph pair from a given version; much of the power of the approach arises because the cross-version variations in the dependence graphs are small, reducing information provided to the programmer. The intellectual merit includes empirical assessment over a broad set of programs and changes, ?value propositions? for using this information, applications of the approach, and use of the partitioning to augment conventional approaches to assessing software complexity. The project addresses two categories of broader impacts: the people directly involved in the research, and the potential for the research to positively affect society through increased programmer productivity.