FlyCatcher infers 300 correct stateful runtime checkers from 400 tests across four systems, yielding 2.6x more correct checkers and 5.2x more error detections than prior work.
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EventADL introduces the first open-box framework for detecting anomalies and localizing root causes in cloud event data by learning semantic and frequency patterns from unlabeled historical events.
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FlyCatcher: Neural Inference of Runtime Checkers from Tests
FlyCatcher infers 300 correct stateful runtime checkers from 400 tests across four systems, yielding 2.6x more correct checkers and 5.2x more error detections than prior work.
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EventADL: Open-Box Anomaly Detection and Localization Framework for Events in Cloud-Based Service Systems
EventADL introduces the first open-box framework for detecting anomalies and localizing root causes in cloud event data by learning semantic and frequency patterns from unlabeled historical events.