[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

A Comparative Study on Combinatorial and Random Testing for Highly Configurable Systems

  • Conference paper
  • First Online:
Testing Software and Systems (ICTSS 2020)

Abstract

Highly configurable systems (HCSs), such as software product lines, have complex configuration spaces. Combinatorial Testing and Random Testing are the main approaches to testing of HCSs. In this paper, we empirically compare their strengths with respect to scalability and diversity of sampled configurations (i.e., tests). We choose Icpl and QuickSampler to respectively represent Combinatorial Testing and Random Testing. Experiments are conducted to evaluate the t-way coverage criterion of generated test suites for HCS benchmarks.

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /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
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 35.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 44.99
Price includes VAT (United Kingdom)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Arcuri, A., Briand, L.C.: Formal analysis of the probability of interaction fault detection using random testing. IEEE Trans. Softw. Eng. 38(5), 1088–1099 (2012)

    Article  Google Scholar 

  2. Chakraborty, S., Fremont, D.J., Meel, K.S., Seshia, S.A., Vardi, M.Y.: On parallel scalable uniform sat witness generation. In: Baier, C., Tinelli, C. (eds.) TACAS 2015. LNCS, vol. 9035, pp. 304–319. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46681-0_25

    Chapter  Google Scholar 

  3. Chen, T.Y., Leung, H., Mak, I.K.: Adaptive random testing. In: Maher, M.J. (ed.) ASIAN 2004. LNCS, vol. 3321, pp. 320–329. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30502-6_23

    Chapter  Google Scholar 

  4. Dutra, R., Laeufer, K., Bachrach, J., Sen, K.: Efficient sampling of SAT solutions for testing. In: Proceedings of ICSE 2018, pp. 549–559 (2018)

    Google Scholar 

  5. Ermon, S., Gomes, C., Selman, B.: Uniform solution sampling using a constraint solver as an oracle. In: Proceedings of UAI 2012, pp. 255–264 (2012)

    Google Scholar 

  6. Gargantini, A., Radavelli, M.: Migrating combinatorial interaction test modeling and generation to the web. In: 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), pp. 308–317, April 2018. https://doi.org/10.1109/ICSTW.2018.00066

  7. Garvin, B.J., Cohen, M.B., Dwyer, M.B.: Evaluating improvements to a meta-heuristic search for constrained interaction testing. Empirical Softw. Eng. 16(1), 61–102 (2011)

    Article  Google Scholar 

  8. Hirasaki, Y., Kojima, H., Tsuchiya, T.: Applying random testing to constrained interaction testing. In: Proceedings of SEKE 2013, pp. 193–198 (2014)

    Google Scholar 

  9. Johansen, M.F., Haugen, O., Fleurey, F.: An algorithm for generating t-wise covering arrays from large feature models. In: Proceedings of SPLC 2012, pp. 46–55 (2012)

    Google Scholar 

  10. Kuhn, D.R., Bryce, R., Duan, F., Ghandehari, L.S., Lei, Y., Kacker, R.N.: Chapter one - combinatorial testing: theory and practice. In: Advances in Computers, vol. 99, pp. 1–66. Elsevier (2015)

    Google Scholar 

  11. Kuhn, D.R., Kacker, R.N., Lei, Y.: Introduction to Combinatorial Testing. CRC Press, Boca Raton (2013)

    MATH  Google Scholar 

  12. Lin, J., Cai, S., Luo, C., Lin, Q., Zhang, H.: Towards more efficient meta-heuristic algorithms for combinatorial test generation. In: Proceedings of ESEC/FSE 2019, pp. 212–222 (2019)

    Google Scholar 

  13. Lynce, I., Silva, J.P.M.: On computing minimum unsatisfiable cores. In: Proceedings of SAT 2004 (2004)

    Google Scholar 

  14. Nanba, T., Tsuchiya, T., Kikuno, T.: Using satisfiability solving for pairwise testing in the presence of constraints. IEICE Trans. 95-A(9), 1501–1505 (2012)

    Google Scholar 

  15. Oh, J., Batory, D.S., Myers, M., Siegmund, N.: Finding near-optimal configurations in product lines by random sampling. In: Proceedings of ESEC/FSE 2017, pp. 61–71 (2017)

    Google Scholar 

  16. Wu, H., Nie, C., Petke, J., Jia, Y., Harman, M.: An empirical comparison of combinatorial testing, random testing and adaptive random testing. IEEE Trans. Softw. Eng. (2018)

    Google Scholar 

  17. Yamada, A., Biere, A., Artho, C., Kitamura, T., Choi, E.: Greedy combinatorial test case generation using unsatisfiable cores. In: Proceedings of ASE 2016, pp. 614–624 (2016)

    Google Scholar 

  18. Yu, L., Lei, Y., Kacker, R.N., Kuhn, D.R.: ACTS: a combinatorial test generation tool. In: Proceedings of ICST 2013, pp. 370–375 (2013)

    Google Scholar 

  19. Yu, L., Duan, F., Lei, Y., Kacker, R., Kuhn, D.R.: Combinatorial test generation for software product lines using minimum invalid tuples. In: Proceedings of HASE 2014, pp. 65–72 (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hao Jin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jin, H., Kitamura, T., Choi, EH., Tsuchiya, T. (2020). A Comparative Study on Combinatorial and Random Testing for Highly Configurable Systems. In: Casola, V., De Benedictis, A., Rak, M. (eds) Testing Software and Systems. ICTSS 2020. Lecture Notes in Computer Science(), vol 12543. Springer, Cham. https://doi.org/10.1007/978-3-030-64881-7_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-64881-7_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64880-0

  • Online ISBN: 978-3-030-64881-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics