Bi-abductive Resource Invariant Synthesis

  • Cristiano Calcagno
  • Dino Distefano
  • Viktor Vafeiadis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5904)

Abstract

We describe an algorithm for synthesizing resource invariants that are used in the verification of concurrent programs. This synthesis employs bi-abductive inference to identify the footprints of different parts of the program and decide what invariant each lock protects. We demonstrate our algorithm on several small (yet intricate) examples which are out of the reach of other automatic analyses in the literature.

Keywords

Shared Variable Concurrent Program Symbolic Execution Synthesis Algorithm Resource Invariant 
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.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Berdine, J., Calcagno, C., O’Hearn, P.: Symbolic execution with separation logic. In: Yi, K. (ed.) APLAS 2005. LNCS, vol. 3780, pp. 52–68. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Berdine, J., Calcagno, C., O’Hearn, P.: Smallfoot: Automatic modular assertion checking with separation logic. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.-P. (eds.) FMCO 2005. LNCS, vol. 4111, pp. 115–137. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Calcagno, C., Distefano, D., O’Hearn, P.W., Yang, H.: Compositional shape analysis by means of bi-abduction. In: POPL. ACM, New York (2009)Google Scholar
  4. 4.
    Chang, B., Rival, X., Necula, G.: Shape analysis with str. invariant checkers. In: Riis Nielson, H., Filé, G. (eds.) SAS 2007. LNCS, vol. 4634, pp. 384–401. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Distefano, D., O’Hearn, P.W., Yang, H.: A local shape analysis based on separation logic. In: Hermanns, H., Palsberg, J. (eds.) TACAS 2006. LNCS, vol. 3920, pp. 287–302. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Gotsman, A., Berdine, J., Cook, B., Sagiv, M.: Thread-modular shape analysis. In: PLDI 2007. ACM, New York (2007)Google Scholar
  7. 7.
    Gulavani, B., Chakraborty, S., Ramalingam, G., Nori, A.: Bottom-up shape analysis. In: Palsberg, J., Su, Z. (eds.) SAS 2009. LNCS, vol. 5679. Springer, Heidelberg (2009)Google Scholar
  8. 8.
    O’Hearn, P.W.: Resources, concurrency and local reasoning. Theoretical Computer Science 375(1-3), 271–307 (2007)MATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Pratikakis, P., Foster, J.S., Hicks, M.: Context-sensitive correlation analysis for detecting races. In: PLDI 2006. ACM, New York (2006)Google Scholar
  10. 10.
    Segalov, M., Lev-Ami, T., Manevich, R., Ramalingam, G., Sagiv, M.: Abstract transformers for thread correlation analysis. In: Hu, Z. (ed.) APLAS 2009. LNCS, vol. 5904, pp. 36–46. Springer, Heidelberg (2009)Google Scholar
  11. 11.
    Yahav, E.: Verifying safety properties of concurrent Java programs using 3-valued logic. In: POPL 2001. ACM, New York (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Cristiano Calcagno
    • 1
  • Dino Distefano
    • 2
  • Viktor Vafeiadis
    • 3
  1. 1.Imperial College 
  2. 2.Queen Mary University of London 
  3. 3.Microsoft Research, Cambridge 

Personalised recommendations