AI RESEARCH
Practical Limits of Autonomous Test Repair: A Multi-Agent Case Study with LLM-Driven Discovery and Self-Correction
arXiv CS.AI
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ArXi:2605.01471v1 Announce Type: cross Maintaining reliable UI test suites in large-scale enterprise applications is a persistent and costly challenge. We present an industrial of a multi-agent autonomous testing system evaluated using anonymized execution data from a production-like enterprise UI testing prototype. The application features several hundred dynamic UI elements per screen.