An All-in-One Toolkit for Automated White-Box Testing

  • Sébastien Bardin
  • Omar Chebaro
  • Mickaël Delahaye
  • Nikolai Kosmatov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8570)


Automated white-box testing is a major issue in software engineering. Over the years, several tools have been proposed for supporting distinct parts of the testing process. Yet, these tools are mostly separated and most of them support only a fixed and restricted subset of testing criteria. We describe in this paper Frama-C/LTest, a generic and integrated toolkit for automated white-box testing of C programs. LTest provides a unified support of many different testing criteria as well as an easy integration of new criteria. Moreover, it is designed around three basic services (test coverage estimation, automatic test generation, detection of uncoverable objectives) covering most major aspects of white-box testing and taking benefit from a combination of static and dynamic analyses. Services can cooperate through a shared coverage database. Preliminary experiments demonstrate the possibilities and advantages of such cooperations.


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  1. 1.
    Ammann, P., Offutt, A.J.: Introduction to software testing. Cambridge University Press (2008)Google Scholar
  2. 2.
    Bardin, S., Kosmatov, N., Cheynier, F.: Efficient Leveraging of Symbolic Execution to Advanced Coverage Criteria. In: ICST 2014. IEEE, Los Alamitos (2014)Google Scholar
  3. 3.
    Chebaro, O., Kosmatov, N., Giorgetti, A., Julliand, J.: Program slicing enhances a verification technique combining static and dynamic analysis. In: SAC 2012. ACM, New York (2012)Google Scholar
  4. 4.
    Cuoq, P., Kirchner, F., Kosmatov, N., Prevosto, V., Signoles, J., Yakobowski, B.: Frama-C - a software analysis perspective. In: Eleftherakis, G., Hinchey, M., Holcombe, M. (eds.) SEFM 2012. LNCS, vol. 7504, pp. 233–247. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Christakis, M., Müller, P., Wüstholz, V.: Collaborative verification and testing with explicit assumptions. In: Giannakopoulou, D., Méry, D. (eds.) FM 2012. LNCS, vol. 7436, pp. 132–146. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Correnson, L., Signoles, J.: Combining Analyses for C Program Verification. In: Stoelinga, M., Pinger, R. (eds.) FMICS 2012. LNCS, vol. 7437, pp. 108–130. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Godefroid, P., Klarlund, N., Sen, K.: DART: Directed Automated Random Testing. In: PLDI 2005. ACM, New York (2005)Google Scholar
  8. 8.
    Godefroid, P., Levin, M.Y., Molnar, D.: Automated Whitebox Fuzz Testing. In: NDSS 2008 (2008)Google Scholar
  9. 9.
    Jamrozik, K., Fraser, G., Tillman, N., de Halleux, J.: Generating Test Suites with Augmented Dynamic Symbolic Execution. In: Veanes, M., Viganò, L. (eds.) TAP 2013. LNCS, vol. 7942, pp. 152–167. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Petiot, G., Kosmatov, N., Giorgetti, A., Julliand, J.: How Test Generation Helps Software Specification and Deductive Verification in Frama-C. In: Seidl, M., Tillmann, N. (eds.) TAP 2014. LNCS, vol. 8570, pp. 204–211. Springer, Heidelberg (2014)Google Scholar
  11. 11.
    Williams, N., Marre, B., Mouy, P.: On-the-Fly Generation of K-Path Tests for C Functions. In: ASE 2004. IEEE, Los Alamitos (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sébastien Bardin
    • 1
  • Omar Chebaro
    • 1
  • Mickaël Delahaye
    • 1
  • Nikolai Kosmatov
    • 1
  1. 1.CEA, LISTGif-sur-YvetteFrance

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