Bounded-Interference Sequentialization for Testing Concurrent Programs

  • Niloofar Razavi
  • Azadeh Farzan
  • Andreas Holzer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7609)


Testing concurrent programs is a challenging problem: (1) the tester has to come up with a set of input values that may trigger a bug, and (2) even with a bug-triggering input value, there may be a large number of interleavings that need to be explored. This paper proposes an approach for testing concurrent programs that explores both input and interleaving spaces in a systematic way. It is based on a program transformation technique that takes a concurrent program P as an input and generates a sequential program that simulates a subset of behaviours of P. It is then possible to use an available sequential testing tool to test the resulting sequential program. We introduce a new interleaving selection technique, called bounded-interference, which is based on the idea of limiting the degree of interference from other threads. The transformation is sound in the sense that any bug discovered by a sequential testing tool in the sequential program is a bug in the original concurrent program. We have implemented our approach into a prototype tool that tests concurrent C# programs. Our experiments show that our approach is effective in finding both previously known and new bugs.


Shared Variable Sequential Program Concurrent Program Testing Tool Coverage Criterion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
  2. 2.
  3. 3.
  4. 4.
  5. 5.
  6. 6.
    Cadar, C., Ganesh, V., Pawlowski, P.M., Dill, D.L., Engler, D.R.: Exe: Automatically generating inputs of death. ACM Trans. Inf. Syst. Secur. 12, 10:1–10:38 (2008)Google Scholar
  7. 7.
    Flanagan, C., Freund, S.N.: Fasttrack: efficient and precise dynamic race detection. Commun. ACM 53, 93–101 (2010)CrossRefGoogle Scholar
  8. 8.
    Godefroid, P., Klarlund, N., Sen, K.: Dart: directed automated random testing. In: PDLI, pp. 213–223. ACM (2005)Google Scholar
  9. 9.
    Lahiri, S.K., Qadeer, S., Rakamarić, Z.: Static and Precise Detection of Concurrency Errors in Systems Code Using SMT Solvers. In: Bouajjani, A., Maler, O. (eds.) CAV 2009. LNCS, vol. 5643, pp. 509–524. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Lal, A., Reps, T.: Reducing concurrent analysis under a context bound to sequential analysis. Form. Methods Syst. Des. 35, 73–97 (2009)zbMATHCrossRefGoogle Scholar
  11. 11.
    Miller, J.C., Maloney, C.J.: Systematic mistake analysis of digital computer programs. Commun. ACM 6, 58–63 (1963)zbMATHCrossRefGoogle Scholar
  12. 12.
    Musuvathi, M., Qadeer, S., Ball, T., Basler, G., Nainar, P.A., Neamtiu, I.: Finding and reproducing heisenbugs in concurrent programs. In: OSDI, pp. 267–280 (2008)Google Scholar
  13. 13.
    Park, C.-S., Sen, K.: Randomized active atomicity violation detection in concurrent programs. In: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of Software Engineering, SIGSOFT 2008/FSE-16, pp. 135–145. ACM, New York (2008)CrossRefGoogle Scholar
  14. 14.
    Park, S., Lu, S., Zhou, Y.: Ctrigger: exposing atomicity violation bugs from their hiding places. In: ASPLOS, pp. 25–36 (2009)Google Scholar
  15. 15.
    Pozniansky, E., Schuster, A.: Multirace: efficient on-the-fly data race detection in multithreaded c++ programs: Research articles. Concurr. Comput.: Pract. Exper. 19, 327–340 (2007)CrossRefGoogle Scholar
  16. 16.
    Qadeer, S., Wu, D.: Kiss: keep it simple and sequential. SIGPLAN Not. 39, 14–24 (2004)CrossRefGoogle Scholar
  17. 17.
    Sen, K.: Race directed random testing of concurrent programs. In: PLDI, pp. 11–21 (2008)Google Scholar
  18. 18.
    Sen, K., Agha, G.: CUTE and jCUTE: Concolic Unit Testing and Explicit Path Model-Checking Tools. In: Ball, T., Jones, R.B. (eds.) CAV 2006. LNCS, vol. 4144, pp. 419–423. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  19. 19.
    Sorrentino, F., Farzan, A., Madhusudan, P.: Penelope: weaving threads to expose atomicity violations. In: FSE 2010, pp. 37–46. ACM (2010)Google Scholar
  20. 20.
    Tillmann, N., de Halleux, J.: Pex–White Box Test Generation for.NET. In: Beckert, B., Hähnle, R. (eds.) TAP 2008. LNCS, vol. 4966, pp. 134–153. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  21. 21.
    La Torre, S., Madhusudan, P., Parlato, G.: Reducing Context-Bounded Concurrent Reachability to Sequential Reachability. In: Bouajjani, A., Maler, O. (eds.) CAV 2009. LNCS, vol. 5643, pp. 477–492. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  22. 22.
    Wang, C., Limaye, R., Ganai, M., Gupta, A.: Trace-Based Symbolic Analysis for Atomicity Violations. In: Esparza, J., Majumdar, R. (eds.) TACAS 2010. LNCS, vol. 6015, pp. 328–342. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  23. 23.
    Yi, J., Sadowski, C., Flanagan, C.: Sidetrack: generalizing dynamic atomicity analysis. In: PADTAD 2009, pp. 8:1–8:10. ACM, New York (2009)Google Scholar
  24. 24.
    Zhang, W., Lim, J., Olichandran, R., Scherpelz, J., Jin, G., Lu, S., Reps, T.: Conseq: detecting concurrency bugs through sequential errors. In: ASPLOS, pp. 251–264 (2011)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Niloofar Razavi
    • 1
  • Azadeh Farzan
    • 1
  • Andreas Holzer
    • 2
  1. 1.University of TorontoCanada
  2. 2.Vienna University of TechnologyAustria

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