Skip to main content

An Approach for Test Case Prioritization Using Harmony Search for Aspect-Oriented Software Systems

  • Conference paper
  • First Online:
Ambient Communications and Computer Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 904))

Abstract

Regression testing is important part of testing during software maintenance. It ensures error-free software after modification during maintenance. Without any priority, execution of test cases is not cost-effective and time-consuming. Therefore, it is highly desirable to prioritize the test cases to achieve maximum fault coverage. In this study, a test case prioritization approach using harmony search for aspect-oriented software systems is proposed. In this paper, we have taken two objective functions such as minimum execution time and maximum fault coverage. Further, average percentage fault detection (APFD) metric was used to validate the results. Further, results are compared with random prioritization and no prioritization. The results indicate that proposed approach is performing well.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • 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

References

  1. Beizer, B.: Software testing techniques, 2nd edn. Dreamtech Press (2003)

    Google Scholar 

  2. Kiczales, G., Hilsdale, E., Hugunin, J., Kersten, M., Palm, J., Griswold, W.: An overview of AspectJ. In: 15th European Conference on Object Oriented programming, Budapest, Hungry (2001)

    Google Scholar 

  3. Ahmed, B.S.: Test case minimization approach using fault detection and combinatorial optimization techniques for configuration-aware structural testing. Int. J. Eng. Sci. Technol. (2015)

    Google Scholar 

  4. Konsaard, P., Lachana, R.: Using artificial bee colony for code coverage based test suite prioritization. In: 2nd International Conference on Information Science and Security (ICISS), pp. 1–4, IEEE (2015)

    Google Scholar 

  5. Raju, S., Uma, G.V.: Factors oriented test case prioritization technique in regression testing using genetic algorithm. Eur. J. Sci. Res. 74(3), 389–402 (2012)

    Google Scholar 

  6. Solanki, K., Singh Y., Dalal S.: Test case prioritization: an approach based on modified ant colony optimization (m-ACO). In: International Conference on Computer Communication and Control (IC4), pp. 1–6. IEEE (2015)

    Google Scholar 

  7. Mohemmed, A.W., Sahoo, N.C., Geok, T.K.: Solving shortest path problem using particle swarm optimization. Appl. Soft Comput. 8(4), 1643–1653 (2008)

    Article  Google Scholar 

  8. Vedpal, C.N., Kumar, H.: A hierarchical test case prioritization technique for object oriented software. In: International Conference on Contemporary Computing and Informatics (IC3I), pp. 249–254 (2014)

    Google Scholar 

  9. Hla, K.H.S.: Applying particle swarm optimization to prioritizing test cases for embedded real time software retesting. In: IEEE 8th International Conference on Computer and Information Technology Workshops, Sydney, Australia, pp. 528–532 (2008)

    Google Scholar 

  10. Malhotra, R., Tiwari, D.: Development of a framework for test case prioritization using genetic algorithm. ACM SIGSOFT Softw. Eng. Notes 38(3), 1–6 (2013)

    Article  Google Scholar 

  11. Mahmood, M.H., Hosain, M.S.: Improving test case prioritization based on practical priority factors. In: 8th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, China (2017)

    Google Scholar 

  12. Gao, D., Guo, X., Zhao, L.: Test case prioritization for regression testing based on ant colony optimization. In: 6th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, China (2015)

    Google Scholar 

  13. Kaur, A., Goyal, S.: A genetic algorithm for regression test case prioritization using code coverage. Int. J. Comput. Sci. Eng. 3(5), 1839–1847 (2011)

    Google Scholar 

  14. Kaur, A., Goyal, S.: A bee colony optimization algorithm for code coverage test suite prioritization. Int. J. Eng. Sci. Technol. 3(4), 2786–2795 (2011)

    Google Scholar 

  15. Singh, Y., Kaur, A., Suri, B.: Test case prioritization using ant colony optimization. ACM SIGSOFT Softw. Eng. Notes 35(4), 1–7 (2010)

    Article  Google Scholar 

  16. Suri, B., Singhal, S.: Analyzing test case selection & prioritization using ACO. ACM SIGSOFT Softw. Eng. Notes 36(6), 1–5 (2011)

    Article  Google Scholar 

  17. Fu, W., Yu, H., Fan, G., Ji, X., Pei, X.: A regression test case prioritization algorithm based on program changes and method invocation relationship. In: 24th Asia-Pacific Software Engineering Conference (APSEC), Nanjing, China (2017)

    Google Scholar 

  18. Luo, Q., Moran, K., Zhang, L., Poshyvanyk, D.: How do static and dynamic test case prioritization techniques perform on modern software systems? An extensive study on GitHub projects. IEEE Trans. Softw. Eng. (2018)

    Google Scholar 

  19. Tiwari, S., Mishra, K.K., Kumar, A., Misra, A.K.: Spectrum-based fault localization in regression testing. In: 2011 Eighth International Conference on Information Technology: New Generations, Las Vegas, NV, pp. 191–195 (2011). https://doi.org/10.1109/itng.2011.4

  20. Tiwari, S., Mishra, K.K., Misra, A.K.: Test case generation for modified code using a variant of particle swarm optimization (PSO) algorithm. In: 2013 10th International Conference on Information Technology: New Generations, Las Vegas, NV, pp. 363–368 (2013). https://doi.org/10.1109/itng.2013.58

  21. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation, Sage Publication 76(2), 60–68 (2001)

    Article  Google Scholar 

  22. Choudhary, A., Baghel, A.S., Sangwan, O.P.: An efficient parameter estimation of software reliability growth models using gravitational search algorithm. Int. J. Syst. Assur. Eng. Manage. 8(1), 79–88 (2017)

    Article  Google Scholar 

  23. Choudhary, A., Agrawal, A.P., Kaur, A.: An effective approach for regression test case selection using pareto based multi-objective harmony search. In: Proceedings of the 11th International Workshop on Search-Based Software Testing, pp. 13–20. ACM (2018)

    Google Scholar 

  24. Laddad, R.: AspectJ in action- enterprise AOP with spring applications, 2nd edn. Manning Publications, Greenwich (2009)

    Google Scholar 

  25. https://www.eclipse.org/

  26. Elbaum, S., Malishevsky, A.G., Rothermel, G.: Test case prioritization: a family of empirical studies. IEEE Trans. Softw. Eng. 28(2), 159–182 (2002)

    Article  Google Scholar 

  27. Rothermel, G., Untch, R.H., Chu, C., Harrold, M.J.: Prioritizing test cases for regression testing. IEEE Trans. Softw. Eng. 27(10), 929–948 (2001)

    Article  Google Scholar 

  28. Do, H., Rothermel, G.: On the use of mutation faults in empirical assessments of test case prioritization techniques. IEEE Trans. Softw. Eng. 32(9), 733–752 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abhishek Singhal .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Singhal, A., Bansal, A., Kumar, A. (2019). An Approach for Test Case Prioritization Using Harmony Search for Aspect-Oriented Software Systems. In: Hu, YC., Tiwari, S., Mishra, K., Trivedi, M. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 904. Springer, Singapore. https://doi.org/10.1007/978-981-13-5934-7_23

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-5934-7_23

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5933-0

  • Online ISBN: 978-981-13-5934-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics