arXiv:2607. 04786v1 Announce Type: cross Abstract: Test maintenance is a critical, yet costly, activity - particularly as codebases rapidly evolve.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
The paper introduces ORACLE‑SWE, a study that systematically evaluates how different intermediate information signals—such as Reproduction Test, Regression Test, Edit Location, Execution Context, and API Usage—contribute to the success of language‑model agents on software engineering tasks. It quantifies the impact of both oracle‑provided signals and those extracted by agents, and measures the performance gap between current agent‑found signals and their oracle counterparts. The authors release code and a dataset to support future signal‑analysis research in this area.
The paper presents a systematic analysis of five state‑of‑the‑art automated program repair agents, tracing their decision‑making across 500 real‑world repair tasks. It finds that while the agents perform well on simple fixes, they struggle with logic‑intensive bugs, often producing verbose, overfitted patches that pass tests without addressing root causes. Key bottlenecks identified include poor test generation, limited regression test selection, and reliance on primitive tooling without access to debuggers or advanced program analysis tools.
arXiv:2509. 24148v3 Announce Type: replace-cross Abstract: Test-Driven Development (TDD) is a widely adopted practice that requires developers to create and execute tests alongside implementation.
SWE‑Nexus is a fully automated pipeline that builds repository‑level implementation tasks by analyzing test execution. It uses four construction agents to select tests, trace production function bodies, and generate behavioral specifications, retaining scopes only when all expected scoring points pass and masking the traced bodies triggers failures. The benchmark covers 600 tasks from 105 repositories in six languages, and the best configuration resolves 37.8% of tasks in a single attempt, demonstrating the system’s ability to construct tasks from validated behavior beyond individual code changes.
arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix ge...
SWEPatchTest is a benchmark that evaluates software tests by measuring their ability to reproduce issues, accept correct patches, and reject incorrect ones across 619 tasks and 82,579 candidate patches. It introduces the Joint Validation Rate metric, revealing that even the best configurations only achieve 9.21% success when all three criteria are met. Using these validation scores to select demonstrations for supervised fine‑tuning can roughly triple the Joint Validation Rate and enhance downstream repair performance on multiple SWE‑bench datasets.