Automatic Test Data Generation Symbolic and Concolic Executions

  • Chapter
  • First Online:
Software Testing Automation

Abstract

Dynamic-symbolic execution is a fantastic area of research from a software industry point of view.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Necula, G. C., McPeak, S., Rahul, S. P., and Weimer, W.: CIL: Intermediate Language and Tools for Analysis and Transformation of C Programs. In: CC’02: Proceedings of the 11th International Conference on Compiler Construction, (London, UK), pp. 213–228. Springer-Verlag (2002)

    Google Scholar 

  2. Necula, G.C.: CIL: Infrastructure for C Program Analysis and Transformation (v. 1.3.7). April 24, 2009, http://www.cs.berkeley.edu/~necula/cil

  3. Luk, C., Cohn, R.S., Muth, R., Patil, H., Klauser, A., Lowney, P.G., Wallace, S., Reddi, V.J., Hazelwood, K.M.: Pin: building customized program analysis tools with dynamic instrumentation. In PLDI'05: Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation, pp. 190–200.

    Google Scholar 

  4. DynamoRio: Dynamic Instrumentation Tool Platform. http://code.google.com/p/dynamorio/

  5. Nethercote, N., Seward, J.: Valgrind: a framework for heavyweight dynamic binary instrumentation. In Ferrante, J., McKinley, K.S. (eds.). PLDI, ACM, 2007, pp. 89–100

    Google Scholar 

  6. STP Constraint Solver. http://sites.google.com/site/stpfastprover/STP-FastProver

  7. Wang, X., Jiang, Y., Tian, W.: An efficient method for automatic generation of linearly independent paths in white-box testing. Int. J. Eng. Technol. Innov. 5(2), 108–120 (2015)

    Google Scholar 

  8. Aho, A., Lam, M.S.: Compilers: Principles, Techniques and tools, 2nd ed. Addison Wesley (2007)

    Google Scholar 

  9. Sen, K.: CUTE : A concolic unit testing engine for C. In: Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering, pp. 263–272 (2005)

    Google Scholar 

  10. Necula, G.C., McPeak, S., Rahul, SP., Weimer, W.: CIL: intermediate language and tools for analysis and transformation of C programs. In: Proceedings of Conference on compiler Construction, pp. 213–228 (2002)

    Google Scholar 

  11. Liu, Y., Zhou, X., Wei-Wei, G.: A survey of search strategies in the dynamic symbolic execution. In: ITM Web Conference, pp. 3–25 (2017)

    Google Scholar 

  12. Godefroid, P., Klarlund, N., Sen, K.: DART: directed automated random testing. ACM Sigplan Notices Vol. 40. No. 6. ACM (2005).

    Google Scholar 

  13. Sen, K., Marinov, D., Agha, G.: CUTE: a concolic unit testing engine for C. In: ACM, SIGSOFT Software Engineering Notes. Vol. 30., No. 5. ACM (2005)

    Google Scholar 

  14. Godefroid, P., Levin, M., Molnar, D., et al.: Automated white box fuzz testing. In: NDSS (2008)

    Google Scholar 

  15. Park, S., Hossain, B.M.M., Hussain, I., Csallner, C., Grechanik, M., Taneja, K., Fu, C., **e, Q.: CarFast: achieving higher statement coverage faster. In: Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, FSE’12 pages 35:1{35:11, New York, NY, USA (2012)

    Google Scholar 

  16. Cadar, C., Engler, D.: Execution generated test cases: how to make systems code crash itself. In: Proceedings of the 12th International Conference on Model Checking Software, Berlin, Heidelberg, (2005)

    Google Scholar 

  17. Kaiser, C.: Quantitative analysis of exploration schedules for symbolic execution, degree project, Kth royal institute of technology, school of computer science and communication Stockholm, Sweden (2017)

    Google Scholar 

  18. Halleux, N.T.J.: Parameterized Unit Testing with Microsoft Pex. In: Proc. The/FSE, pp. 253–262 (2005)

    Google Scholar 

  19. Tillmann, T.X.N.: Fitness-guided path exploration in dynamic symbolic execution. In: IEEE/IFIP International Conference on Dependable Systems & Networks (2009)

    Google Scholar 

  20. Ball, T., Daniel, J.: Deconstructing dynamic symbolic execution, Technical report, Jan. (2015)

    Google Scholar 

  21. BeaEngine Sweet Home, http://beatrix2004.free.fr/BeaEngine/index1.php

  22. Bergmann, V.: Feed4JUnit Homepage. http://databene.org/feed4junit (2011)

  23. Pathfinder, J.: A Model Checker for Java Programs, [Online]. http://ase.arc.nasa.gov/visser/jpf/

  24. CROWN: Concolic testing for Real-wOrld, https://github.com/swtv-kaist/CROWN

  25. Downey, A., Monje, N.: Think Ocaml: how to think like a (functional) computer scientist. Green Tea Press (2008)

    Google Scholar 

  26. Oliveira, M. R.: How design patterns can help you in develo** unit testing-enabled applications (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saeed Parsa .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Parsa, S. (2023). Automatic Test Data Generation Symbolic and Concolic Executions. In: Software Testing Automation. Springer, Cham. https://doi.org/10.1007/978-3-031-22057-9_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-22057-9_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22056-2

  • Online ISBN: 978-3-031-22057-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Navigation