Model-based fault localization in large-scale computing systems

We propose a new fault localization technique for software bugs in large-scale computing systems. Our technique always collects per-process function call traces of a target system, and derives a concise execution model that reflects its normal function calling behaviors using the traces. To find the cause of a failure, we compare the derived model with the traces collected when the system failed, and compute a suspect score that quantifies how likely a particular part of call traces explains the failure. The execution model consists of a call probability of each function in the system that we estimate using the normal traces. Functions with low probabilities in the model give high anomaly scores when called upon a failure. Frequently-called functions in the model also give high scores when not called. Finally, we report the function call sequences ranked with the suspect scores to the human analyst, narrowing further manual localization down to a small part of the overall system. W...

• Type: Conference
• Year: 2008
• Where: IPPS
• Authors: Naoya Maruyama, Satoshi Matsuoka
• Keywords: Distributed And Parallel Computing, Execution Model, Fault Localization, Fault Localization Technique, IPPS 2008