Localizing concurrency faults that occur in production is hard because, (1) detailed field data, such as user input, file content and interleaving schedule, may not be available to developers to reproduce the failure; (2) it is often impractical to assume the availability of multiple failing executions to localize the faults using existing techniques; (3) it is challenging to search for buggy locations in an application given limited runtime data; and, (4) concurrency failures at the system level often involve multiple processes or event handlers (e.g., software signals), which can not be handled by existing tools for diagnosing intra-process(thread-level) failures. To address these problems, we present SCMiner, a practical online bug diagnosis tool to help developers understand how a system-level concurrency fault happens based on the logs collected by the default system audit tools. SCMiner achieves online bug diagnosis to obviate the need for offline bug reproduction. SCMiner does not require code instrumentation on the production system or rely on the assumption of the availability of multiple failing executions. Specifically, after the system call traces are collected, SCMiner uses data mining and statistical anomaly detection techniques to identify the failure-inducing system call sequences. It then maps each abnormal sequence to specific application functions. We have conducted an empirical study on 19 real-world benchmarks. The results show that SCMiner is both effective and efficient at localizing system-level concurrency faults.
|Title of host publication||Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019|
|Number of pages||12|
|State||Published - Nov 2019|
|Event||34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019 - San Diego, United States|
Duration: Nov 10 2019 → Nov 15 2019
|Name||Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019|
|Conference||34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019|
|Period||11/10/19 → 11/15/19|
Bibliographical noteFunding Information:
This research is supported in part by the NSF grant CCF-1652149.
© 2019 IEEE.
- Concurrency Failures
- Fault Localization
- Multi Process Applications
ASJC Scopus subject areas
- Computer Networks and Communications
- Control and Optimization