A Universal Textual Merge Strategy Based on Tokens for Version Control Systems

TL;DR

Summer is a novel token-based merge algorithm for version control that reduces conflicts and improves merge accuracy across diverse file types without relying on language-specific parsers.

Contribution

It introduces a language-agnostic, token-level merging approach that models code refactorings and parallel edits more effectively than traditional line-based methods.

Findings

Summer achieved 36% accuracy in reproducing developer merges verbatim.

It ranked second in semantic accuracy among five merge tools.

The approach is effective across Java and non-Java files.

Abstract

Merging is a core operation in version control systems such as Git, but traditional line-based algorithms often yield spurious conflicts, particularly in the presence of refactorings or parallel edits. While syntax- and semantics-aware merging approaches can reduce conflicts, they introduce drawbacks such as loss of formatting, dependence on language-specific parsers, and limited flexibility across heterogeneous artifacts. To address this gap, we present Summer, a novel textual token-based merge algorithm independent of document formats. Dividing text into tokens, our approach formulates token-level changes in one branch into string-rewriting rules and move rules, and applies these rules to the text of the other branch to construct a merge. Despite being independent on programming languages, our move rules model extracting and inlining functions. We evaluated Summer on ConflictBench, a large benchmark of real-world merge scenarios, comparing it with five pioneering merge tools across Java and non-Java files. Experimental results show that Summer achieved the highest 36% accuracy in reproducing merges verbatim identical to developers', and ranked second in semantic accuracy.