A Global Author-Identity Map for the World of Code:62.7M Developer Identities from 106.8M Author Strings over 5.87B Commits

2026-07-07

AI Summary

This work addresses the pervasive identity ambiguity in global code repositories—where individual developers use multiple accounts or identical identifiers are reused by different contributors—by proposing a high-precision identity disambiguation method. The approach constructs a global identity mapping spanning 5.87 billion commits, leveraging non-transitive clustering, a refined identity classification scheme (good/bad/local/bot/partial), project context restoration, and cross-commit provenance tracing. It successfully consolidates 107 million raw author strings into 62.7 million canonical identities while mitigating over-merging artifacts such as “giant clusters.” Evaluated on the ALFAA gold-standard benchmark, the method achieves a recall of 0.70 and precision of 0.88. Notably, 73.5% of commits are attributed to multi-string identities, and coverage of human developers increases to 98.17%.

Abstract

Mining software repositories at global scale founders on author identity: the same developer commits under many name/email strings, and the same string is reused by many developers. We release a curated author-identity map for World of Code (WoC) version V2604, covering all 5,866,595,698 commits. It ships four co-versioned artifacts: a global alias map (a2AFullSUG) folding 106,826,059 raw author/committer strings into canonical identities; a per-identity classification (A2clsFull) tagging each id good, bad-by-attribute, local, bot, or partial; a within-project table (P2aAFull) recovering low-quality ids inside the one project where their reuse is unambiguous; and a commit-to-identity table (c2AFull) tagging every commit with its resolution provenance. The map is mega-cluster free, its largest cluster 6,910 ids (one GitHub noreply identity), and it resolves 73.5% of six billion commits into multi-id identities, raising human-id commit coverage to 98.17%. The design problem is clumping, not recall: a naive transitive union over shared-attribute edges welds three million unrelated people into one cluster, an over-merge that recall-only benchmarks price at zero. We report both error families, splitting and clumping, and show the high precision claimed by global-scale union maps can be an artifact of never measuring the conflated region. Against the ALFAA human-rated gold set the map scores recall 0.70 / precision 0.88, where the prior WoC map's apparent 0.95 precision collapses to 0.52 once its 3,006,318-id mega-cluster is counted. A canonical software-author identity is also a cross-corpus join key to scholarly author graphs, where clumping is again the binding constraint. All artifacts ship with the WoC V2604 release and a self-contained replication package.

Problem

• author identity
• software repositories
• identity resolution
• commit attribution
• developer identification

Innovation

• author disambiguation
• identity resolution
• software repository mining
• mega-cluster avoidance
• precision-recall tradeoff