AI RESEARCH
AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation
arXiv CS.AI
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ArXi:2605.12925v1 Announce Type: cross Evaluation of software engineering (SWE) agents is dominated by a binary signal: whether the final patch passes the tests. This outcome-only view treats a principled solution and a chaotic trial-and-error process as equivalent. We show that this equivalence is empirically false. We evaluate 2,614 OpenHands trajectories from eight model backends on 60 SWE-bench Verified tasks. Of these, 47 have enough passing trajectories to construct task-level process references, yielding a 1,815-trajectory evaluation subset.