SPARK improves LLM-based test code fault localization by retrieving similar past faults and selectively annotating suspicious lines in new failing tests.
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Traditional ML models on bug report text outperform fine-tuned transformers for fault localization in industrial software using five years of ABB Robotics data.
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Similar Pattern Annotation via Retrieval Knowledge for LLM-Based Test Code Fault Localization
SPARK improves LLM-based test code fault localization by retrieving similar past faults and selectively annotating suspicious lines in new failing tests.
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Bug-Report-Driven Fault Localization: Industrial Benchmarking and Lesson Learned at ABB Robotics
Traditional ML models on bug report text outperform fine-tuned transformers for fault localization in industrial software using five years of ABB Robotics data.