Concurrency bug detection through improved pattern matching using semantic information

Abstract

Many software systems today are concurrent programs as multi-core processors become popular. However, the correctness of an industrial-size concurrent program (e.g. operating system) is difficult to achieve by the traditional testing or model checking technique. In this research, we propose a light-weight concurrency bug detection technique based on bug pattern matching targeting for Linux kernel source code. In order to understand concurrency bugs (e.g. deadlock, data race), we first survey the previously reported bugs detected from Linux file systems, and then classify the bugs with respect to the five attributes: symptom, fault, resolution, synchronization primitives, and synchronization granularity. Second, we identify ten concurrency bug patterns. And then we develop the bug pattern detectors and applied to the Linux file systems. Finally, and foremost, we improve the accuracy of the concurrency bug detection technique by enhancing semantic information in pattern matching. We demonstrate the effectiveness of our technique through detection of concurrency bugs in the Linux file systems.