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ARISE toolset enhances AI agents for code fault localization and repair

Researchers have developed ARISE, a new system designed to improve the accuracy of AI agents in localizing and repairing software faults. ARISE enhances large language models by providing a detailed program graph that includes data-flow information, enabling agents to trace variable usage more precisely. Evaluations on SWE-bench Lite demonstrated significant improvements in fault localization and repair success rates compared to existing baselines. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Enhances AI agent capabilities for software development, potentially improving code quality and developer productivity.

RANK_REASON This is a research paper detailing a new system and its evaluation on a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Shahd Seddik, Fatemeh Fard ·

    ARISE: A Repository-level Graph Representation and Toolset for Agentic Fault Localization and Program Repair

    arXiv:2605.03117v1 Announce Type: cross Abstract: Repository-level fault localization (FL) and automated program repair (APR) require an agent to identify the relevant code units across files, follow call and data dependencies, and generate a valid patch. Existing graph-based sys…