Detecting Semantic Conflicts using Static Analysis

TL;DR

This paper introduces a static analysis-based technique to detect semantic conflicts during code merging, addressing limitations of existing tools that only identify textual conflicts, and demonstrates its effectiveness on a dataset of real merge scenarios.

Contribution

The paper presents a novel static analysis approach for detecting semantic conflicts in code merges, outperforming previous dynamic analysis methods in recall and F1 score.

Findings

Outperforms previous dynamic analysis methods in F1 score and recall

Achieves comparable precision to static analysis and theorem proving approaches

Demonstrates effectiveness on a dataset of 99 merge scenarios

Abstract

Version control system tools empower developers to independently work on their development tasks. These tools also facilitate the integration of changes through merging operations, and report textual conflicts. However, when developers integrate their changes, they might encounter other types of conflicts that are not detected by current merge tools. In this paper, we focus on dynamic semantic conflicts, which occur when merging reports no textual conflicts but results in undesired interference - causing unexpected program behavior at runtime. To address this issue, we propose a technique that explores the use of static analysis to detect interference when merging contributions from two developers. We evaluate our technique using a dataset of 99 experimental units extracted from merge scenarios. The results provide evidence that our technique presents significant interference detection capability. It outperforms, in terms of F1 score and recall, previous methods that rely on dynamic analysis for detecting semantic conflicts, but these show better precision. Our technique precision is comparable to the ones observed in other studies that also leverage static analysis or use theorem proving techniques to detect semantic conflicts, albeit with significantly improved overall performance.