SCMiner: Localizing System-Level Concurrency Faults from Large System Call Traces
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 cannot 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.
Preprint (Scminer_preprint.pdf) | 486KiB |
Presentation Slides (Zaman_v2.pptx) | 2.41MiB |
Wed 13 Nov Times are displayed in time zone: Tijuana, Baja California change
13:40 - 15:20: Systems and LocalizationPapers / Industry Showcase / Research Papers / Demonstrations at Cortez 2&3 Chair(s): Tegawendé F. BissyandéSnT, University of Luxembourg | |||
13:40 - 14:00 Talk | Combining Spectrum-Based Fault Localization and Statistical Debugging: An Empirical Study Research Papers Jiajun JiangPeking University, Ran WangPeking University, Yingfei XiongPeking University, Xiangping ChenSun Yat-sen University, Lu ZhangPeking University Pre-print | ||
14:00 - 14:20 Talk | SCMiner: Localizing System-Level Concurrency Faults from Large System Call Traces Research Papers Tarannum Shaila ZamanUniversity of Kentucky, Xue HanUniversity of Kentucky, Tingting YuUniversity of Kentucky Pre-print File Attached | ||
14:20 - 14:40 Talk | Root Cause Localization for Unreproducible Builds via Causality Analysis over System Call Tracing Research Papers Zhilei RenDalian University of Technology, Changlin LiuCase Western Reserve University, Xusheng XiaoCase Western Reserve University, He JiangSchool of Software, Dalian University of Technology, Tao XiePeking University | ||
14:40 - 15:00 Talk | PTracer: A Linux Kernel Patch Trace Bot Industry Showcase | ||
15:00 - 15:10 Demonstration | Pangolin: An SFL-based Toolset for Feature Localization Demonstrations Bruno Miguel Sotto-Mayor de Castro MachadoIST, University of Lisbon, Alexandre PerezPalo Alto Research Center, Rui AbreuInstituto Superior Técnico, U. Lisboa & INESC-ID | ||
15:10 - 15:20 Demonstration | SiMPOSE - Configurable N-Way Program Merging Strategies for Superimposition-based Analysis of Variant-Rich Software Demonstrations Dennis ReulingSoftware Engineering Group, University of Siegen, Udo KelterSoftware Engineering Group, University of Siegen, Sebastian RulandTU Darmstadt, Real-time Systems Lab, Malte LochauTU Darmstadt Pre-print Media Attached File Attached |