Abstract
In parallel programs concurrency bugs are often caused by unsynchronized accesses to shared memory locations, which are called data races. In order to support programmers in writing correct parallel programs, it is therefore highly desired to have tools on hand that automatically detect such data races. Today, most of these tools only consider unsynchronized read and write operations on a single memory location. Concurrency bugs that involve multiple accesses on a set of correlated variables may be completely missed. Tools may overwhelm programmers with data races on various memory locations, without noticing that the locations are correlated. In this paper, we propose a novel approach to data race detection that automatically infers sets of correlated variables and logical operations by analyzing data and control dependencies. For data race detection itself, we combine a modified version of the lockset algorithm with happens-before analysis providing the first hybrid, dynamic race detector for correlated variables. We implemented our approach on top of the Valgrind, a framework for dynamic binary instrumentation. Our evaluation confirmed that we can catch data races missed by existing detectors and provide additional information for correct bug fixing.
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References
Lu, S., Park, S., Seo, E., Zhou, Y.: Learning from mistakes: a comprehensive study on real world concurrency bug characteristics. In: ASPLOS XIII: Proceedings of the 13th International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 329–339. ACM, New York (2008)
Savage, S., Burrows, M., Nelson, G., Sobalvarro, P., Anderson, T.: Eraser: a dynamic data race detector for multithreaded programs. ACM Trans. Comput. Syst. 15(4), 391–411 (1997)
Jannesari, A., Tichy, W.: Identifying ad-hoc synchronization for enhanced race detection. In: 2010 IEEE International Symposium on Parallel Distributed Processing (IPDPS), pp. 1–10 (19-23, 2010)
Jannesari, A., Bao, K., Pankratius, V., Tichy, W.F.: Helgrind+: An efficient dynamic race detector. In: International on Parallel and Distributed Processing Symposium, pp. 1–13 (2009)
Jannesari, A., Tichy, W.F.: On-the-fly race detection in multi-threaded programs. In: PADTAD 2008: Proceedings of the 6th Workshop on Parallel and Distributed Systems, pp. 1–10. ACM, New York (2008)
Yu, Y., Rodeheffer, T., Chen, W.: Racetrack: efficient detection of data race conditions via adaptive tracking. SIGOPS Oper. Syst. Rev. 39(5), 221–234 (2005)
Hammer, C., Dolby, J., Vaziri, M., Tip, F.: Dynamic detection of atomic-set-serializability violations. In: ICSE 2008: Proceedings of the 30th International Conference on Software Engineering, pp. 231–240. ACM, New York (2008)
Vaziri, M., Tip, F., Dolby, J.: Associating synchronization constraints with data in an object-oriented language. In: POPL 2006: Conference Record of the 33rd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pp. 334–345. ACM, New York (2006)
Bernstein, P.A., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley, Reading (1987)
Lu, S., Park, S., Hu, C., Ma, X., Jiang, W., Li, Z., Popa, R.A., Zhou, Y.: Muvi: automatically inferring multi-variable access correlations and detecting related semantic and concurrency bugs. In: SOSP 2007: Proceedings of Twenty-First ACM SIGOPS Symposium on Operating Systems Principles, pp. 103–116. ACM, New York (2007)
Xu, M., BodÃk, R., Hill, M.D.: A serializability violation detector for shared-memory server programs. SIGPLAN Not. 40(6), 1–14 (2005)
Collins, J.D., Tullsen, D.M., Wang, H.: Control flow optimization via dynamic reconvergence prediction. In: MICRO 37: Proceedings of the 37th Annual IEEE/ACM International Symposium on Microarchitecture, pp. 129–140. IEEE Computer Society, Washington, DC, USA (2004)
Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21(7), 558–565 (1978)
Fidge, J.: Timestamps in Message Passing Systems that Preserve the Partial Ordering. In: Proc. 11th Australian Computer Science Conf., pp. 55–66 (1988)
Nethercote, N., Seward, J.: Valgrind: a framework for heavyweight dynamic binary instrumentation. SIGPLAN Not. 42(6), 89–100 (2007)
Nethercote, N., Seward, J.: Valgrind: A program supervision framework (2003), http://valgrind.org/
Butenhof, D.R.: Programming with POSIX Threads. ser. Professional Computing Series. Addison-Wesley, Reading (1997)
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Jannesari, A., Westphal-Furuya, M., Tichy, W.F. (2011). Dynamic Data Race Detection for Correlated Variables. In: Xiang, Y., Cuzzocrea, A., Hobbs, M., Zhou, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2011. Lecture Notes in Computer Science, vol 7016. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24650-0_3
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DOI: https://doi.org/10.1007/978-3-642-24650-0_3
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