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SWE-Nexus: Automated Composition of Software Engineering Tasks from Test Execution

arXiv 2610.20038 ↗First posted 14 Oct 2026cs.SE cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 30 references that are in the map. First posted on arXiv 14 Oct 2026.

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13 of 30 references.

References · 13

  1. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  2. 2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 2,004
  3. 2026GLM-5: from Vibe Coding to Agentic Engineeringcited by 587
  4. 2022CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learningcited by 358
  5. 2024Training Software Engineering Agents and Verifiers with SWE-Gymcited by 336
  6. 2025SWE-smith: Scaling Data for Software Engineering Agentscited by 285
  7. 2025SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolutioncited by 263
  8. 2025Multi-SWE-bench: A Multilingual Benchmark for Issue Resolvingcited by 171
  9. 2025SWE-rebench: An Automated Pipeline for Task Collection and Decontaminated Evaluation of Software Engineering Agentscited by 142
  10. 2025Toward Training Superintelligent Software Agents through Self-Play SWE-RLcited by 40
  11. 2024BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studiescited by 36
  12. 2026FeatureBench: Benchmarking Agentic Coding for Complex Feature Developmentcited by 34
1 more
  1. 2026SWE-rebench V2: Language-Agnostic SWE Task Collection at Scalecited by 29

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