SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pass functional tests and overlook review-derived acceptance constraints (review constraints) that often influence whether a patch is acceptable in real-world software development. We introduce SWE-Gate, a repository-level benchmark for software engineering agents that explicitly evaluates review constraint compliance alongside functional correctness. SWE-Gate derives review constraints from real pull request review comments and synthesizes repository-level repair instances around these constraints. Each instance provides separate functional and constraint tests, together with non-compliant and gold patches, enabling explicit separation between issue resolution capability and review constraint compliance. We construct SWE-Gate with 303 repository-level repair instances spanning 75 open-source Python repositories across diverse software domains. Experiments with four LLM backends spanning different capability levels under a common coding-agent scaffold reveal a substantial gap between functional success and success under the complete repair specification: among 644 repairs that pass the functional tests, 221 fail to satisfy the provided review constraints. These findings show that functional-only evaluation overestimates agents' ability to satisfy the full requirements of repository-level repair tasks. The replication package including code, data, and experimental results is available at https://github.com/DeepSoftwareAnalytics/SWE-Gate.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 38 of its 52 references that are in the map. First posted on arXiv 3 Sep 2026.
Builds on
38 of 52 references.
Closest ancestors · 7
Same direction, newest first
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- 2025UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench10 Jun
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- 2025SWE-smith: Scaling Data for Software Engineering Agents30 Apr
- 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agents23 Jul
- 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering6 May
- 2024MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution26 Mar
Other references · 31
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19 more
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- 2026AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code Completioncited by 7
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- 2025SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarkscited by 6
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