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This paper introduces an automated method for building repository-level software engineering benchmarks from test execution traces, rather than from historical code changes. The resulting 600-task benchmark covers 105 repositories and six languages, and the best of 12 evaluated models resolves 37.8% of tasks in one attempt, a useful baseline for coding-agent evaluation. Readers should note that the reported scores depend on the three agent scaffolds tested and on the construction pipeline's own validity checks, which remain to be independently assessed.
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SWE-Nexus: Automated Composition of Software Engineering Tasks from Test Execution

arXiv2 min read

arXiv:2610.20038v2 Announce Type: replace-cross Abstract: Historical code changes provide convenient task boundaries, but do not identify which production functions selected tests exercise or support composing validated behaviors beyond a single change. We present SWE-Nexus, a fully automated pipeline that constructs repository-level implementation tasks from test execution. Four construction agents select tests, adapt tracing and evaluation protocols to each repository, and generate behavioral specifications. For each selected test file, tracing records an observed execution footprint of production function bodies. A scope is retained only if all expected scoring points pass in the original repository and masking the traced bodies causes at least one failure or error. Compatible scopes are composed deterministically, with shared functions counted once and every constituent test file revalidated under the complete combined mask. The benchmark contains 600 tasks from 105 repositories across six programming languages, including 116 atomic and 484 composite tasks. We evaluate 12 models under three agent scaffolds. The best configuration resolves 37.8% of tasks in one attempt, and scope-weighted scoring measures partial recovery. SWE-Nexus enables task construction from validated behavior beyond individual historical changes.

Abstract:Historical code changes provide convenient task boundaries, but do not identify which production functions selected tests exercise or support composing validated behaviors beyond a single change. We present SWE-Nexus, a fully automated pipeline that constructs repository-level implementation tasks from test execution. Four construction agents select tests, adapt tracing and evaluation protocols to each repository, and generate behavioral specifications. For each selected test file, tracing records an observed execution footprint of production function bodies. A scope is retained only if all expected scoring points pass in the original repository and masking the traced bodies causes at least one failure or error. Compatible scopes are composed deterministically, with shared functions counted once and every constituent test file revalidated under the complete combined mask. The benchmark contains 600 tasks from 105 repositories across six programming languages, including 116 atomic and 484 composite tasks. We evaluate 12 models under three agent scaffolds. The best configuration resolves 37.8% of tasks in one attempt, and scope-weighted scoring measures partial recovery. SWE-Nexus enables task construction from validated behavior beyond individual historical changes.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

arXiv:2610.20038 [cs.SE]

(or arXiv:2610.20038v2 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2610.20038 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 270 words

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