Traditional ML models on bug report text outperform fine-tuned transformers for fault localization in industrial software using five years of ABB Robotics data.
arXiv preprint arXiv:2209.14876 (2022)
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An explainable AI system maps student programming errors to instructor-defined misconceptions and delivers instructor-authored feedback, shown through expert review and classroom use to be accurate and well-received.
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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.
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An Explainable AI Assistant for Introductory Programming Education: Improving Feedback Reliability with Instructor-AI Collaboration
An explainable AI system maps student programming errors to instructor-defined misconceptions and delivers instructor-authored feedback, shown through expert review and classroom use to be accurate and well-received.