Efficient concurrency-bug detection across inputs

  • Authors:

  • Dongdong Deng;Wei Zhang;Shan Lu

  • Affiliations:

  • University of Wisconsin, Madison, Madison, WI, USA;University of Wisconsin, Madison, Madison, WI, USA;University of Wisconsin, Madison, Madison, WI, USA

  • Venue:
  • Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
  • Year:
  • 2013

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Abstract

In the multi-core era, it is critical to efficiently test multi-threaded software and expose concurrency bugs before software release. Previous work has made significant progress in detecting and validating concurrency bugs under a given input. Unfortunately, software testing always faces large sets of test inputs, and existing techniques are still too expensive to be applied to every test input in practice. In this paper, we use open-source software to study how existing concurrency-bug detection tools work for a set of inputs. The study shows that an interleaving pattern, such as a data race or an atomicity violation, can often be exposed by many inputs. Consequently, existing bug detectors would inevitably waste their bug detection effort to generate duplicate bug reports, when applied to a set of inputs. Guided by the above study, we propose a coverage metric, Concurrent Function Pairs (CFP), to efficiently approximate how interleavings overlap across inputs. Using CFP, we have designed a new approach to detecting data races and atomicity-violation bugs for a set of inputs. Our evaluation on open-source C/C++ applications shows that our CFP-guided approach can effectively accelerate concurrency-bug detection for a set of inputs by reducing redundant detection effort across inputs.