The Impact of Structure on Software Merging: Semistructured Versus Structured Merge Merge conflicts often occur when developers concurrently change the same code artifacts. While state of practice unstructured merge tools (e.g Git merge) try to automatically resolve merge conflicts based on textual similarity, semistructured and structured merge tools try to go further by exploiting the syntactic structure and semantics of the artifacts involved. Although there is evidence that semistructured merge has significant advantages over unstructured merge, and that structured merge reports significantly fewer conflicts than unstructured merge, it is unknown how semistructured merge compares with structured merge. To help developers decide which kind of tool to use, we compare semistructured and structured merge in an empirical study by reproducing more than 40,000 merge scenarios from more than 500 projects. In particular, we assess how often the two merge strategies report different results, we identify conflicts incorrectly reported by one but not by the other (false positives), and conflicts correctly reported by one but missed by the other (false negatives). Our results show that semistructured and structured merge differ in 24% of the scenarios with conflicts. Semistructured merge reports more false positives, whereas structured merge has more false negatives. Finally, we found that adapting a semistructured merge tool to resolve a particular kind of conflict makes semistructured and structured merge even closer.

Semistructured Merge in JavaScript Systems Industry widely uses unstructured merge tools that rely on textual analysis to detect and resolve conflicts between code contributions. Semistructured merge tools go further by partially exploring the syntactic structure of code artifacts, and, as a consequence, obtaining significant merge accuracy gains for Javalike languages. To understand whether semistructured merge and the observed gains generalize to other kinds of languages, we implement two semistructured merge tools for JavaScript, and compare them to an unstructured tool. We find that current semistructured merge algorithms and frameworks are not directly applicable for scripting languages like JavaScript. By adapting the algorithms, and studying 10,345 merge scenarios from 50 JavaScript projects on GitHub, we find evidence that our JavaScript tools report fewer spurious conflicts than unstructured merge, without compromising the correctness of the merging process. The gains, however, are much smaller than the ones observed for Javalike languages, suggesting that semistructured merge advantages might be limited for languages that allow both commutative and noncommutative declarations at the same syntactic level.