Advertisement

A Literature Survey of Applications of Meta-heuristic Techniques in Software Testing

  • Neha Prabhakar
  • Abhishek Singhal
  • Abhay Bansal
  • Vasundhara Bhatia
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 731)

Abstract

Software testing is a phenomenon of testing the entire software with the objective of finding defects in the software and to judge the quality of the developed system. The performance of the system is degraded if bugs are present in the system. Various meta-heuristic techniques are used in the software testing for its automation and optimization of testing data. This survey paper demonstrates the review of various studies, which used the concept of meta-heuristic techniques in software testing.

Keywords

Software testing Ant colony optimization (ACO) Genetic algorithm (GA) Bugs Test cases Optimization 

References

  1. 1.
    Mayan, J.A., Ravi, T.: Test case optimization using hybrid search. In: International Conference on Interdisciplinary Advances in Applied Computing. New York, NY, USA (2014)Google Scholar
  2. 2.
    Mahajan, M., Kumar, S., Porwal, R.: Applying genetic algorithm to increase the efficiency of a data flow-based test data generation approach. ACM SIGSOFT Softw. Eng. Notes (2012) (New York, NY, USA)Google Scholar
  3. 3.
    Binder, R.V.: Testing Object-Oriented Systems: Models, Patterns, and Tools, 1st edn. Addison-Wesley Professional (1999)Google Scholar
  4. 4.
    Li, H., Lam, C.P.: An ant colony optimization approach to test sequence generation for statebased software testing. In: Proceedings of Fifth International Conference on Quality Software. Melbourne, pp. 255–262 (2005)Google Scholar
  5. 5.
    Rao, K.K., Raju, G.S.V.P., Nagaraj, S.: Optimizing the software testing efficiency by using a genetic algorithm—a design methodology. ACM SIGSOFT Softw. Eng. Notes 38, 10 (2013). New York, NY, USACrossRefGoogle Scholar
  6. 6.
    Mala, J.D., Mohan, V.: IntelligenTester-software test sequence optimization using graph based intelligent search agent. In: Computational Intelligence and Multimedia Applications. Sivakasi, Tamil Nadu (2007)Google Scholar
  7. 7.
    Roper, M., Maclean, I., Brooks, A., Miller, J., Wood, M.: Genetic Algorithms and the Automatic Generation of Test Data (1995)Google Scholar
  8. 8.
    Srivastava, P.R., Gupta, P., Arrawatia, Y., Yadav, S.: Use of genetic algorithm in generation of feasible test data. ACM SIGSOFT Softw. Eng. Notes 34 (2009)Google Scholar
  9. 9.
    Rathore, A., Bohara, A., Gupta, P.R., Lakshmi, P.T.S., Srivastava, P.R.: Application of genetic algorithm and tabu search in software testing. In: Fourth Annual ACM Bangalore Conference (2011)Google Scholar
  10. 10.
    Prakash, S.S.K., Dhanyamraju Prasad, S.U.M., Gopi Krishna, D.: Recommendation and regression test suite optimization using heuristic algorithms. In: 8th India Software Engineering Conference (2015)Google Scholar
  11. 11.
    Bhasin, H.: Artificial life and cellular automata based automated test case generator. ACM SIGSOFT Softw. Eng. Notes 39 (2014)CrossRefGoogle Scholar
  12. 12.
    Khor, S., Grogono, P.: Using a genetic algorithm and formal concept analysis to generate branch coverage test data automatically. In: 19th IEEE International Conference on Automated Software Engineering (2004)Google Scholar
  13. 13.
    Srivastava, P.R., Ramachandran, V., Kumar, M., Talukder, G., Tiwari, V., Sharma, P.: Generation of test data using meta-heuristic approach. In: TENCON 2008 IEEE Region 10 Conference. Hyderabad (2008)Google Scholar
  14. 14.
    Donghua, C., Wenjie, Y.: The research of test-suite reduction technique. In: Consumer Electronics, Communications and Networks (CECNet). XianNing (2011)Google Scholar
  15. 15.
    Singh, Y., Kaur, A., Suri, B.: Test case prioritization using ant colony optimization. ACM SIGSOFT Softw. Eng. Notes 35 (2010)CrossRefGoogle Scholar
  16. 16.
    Srivastava, P.R.: Structured testing using Ant colony optimization. In: First International Conference on Intelligent Interactive Technologies and Multimedia (2010)Google Scholar
  17. 17.
    Suri, B., Singhal, S.: Analyzing test case selection & prioritization using ACO. ACM SIGSOFT Softw. Eng. Notes 36 (2011)CrossRefGoogle Scholar
  18. 18.
    Yi, M.: The research of path oriented test data generation based on a mixed Ant colony system algorithm and genetic algorithm. In: Wireless Communications, Networking, and Mobile Computing (WiCOM). Shanghai (2012)Google Scholar
  19. 19.
    Gulia, P., Chillar, R.S.: A new approach to generate and optimize test cases for uml state diagram using genetic algorithm. ACM SIGSOFT Softw. Eng. Notes 37 (2012)CrossRefGoogle Scholar
  20. 20.
    Varshney, S., Mehrotra, M.: Search based software test data generation for structural testing: a perspective. ACM SIGSOFT Softw. Eng. Notes 38 (2013)CrossRefGoogle Scholar
  21. 21.
    Li, K., Zhang, Z., Liu, W.: Automatic test data generation based on ant colony optimization, vol. 6. Tianjin (2009)Google Scholar
  22. 22.
    Noguchi, T., Washizaki, H., Fukazawa, Y., Sato, A., Ota, K.: History-based test case prioritization for black box testing using ant colony optimization. Graz (2015)Google Scholar
  23. 23.
    Srivastava, P.R., Baby, K.: Automated software testing using meta-heuristic technique based on an Ant colony optimization. In: Electronic System Design (ISED). Bhubaneswar (2010)Google Scholar
  24. 24.
    Talbi, E.G.: Meta Heuristic from Design to Implementation. Wiley, Hoboken, New Jersey (2009)MATHGoogle Scholar
  25. 25.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co. Inc., Boston, MA, USA (1989)MATHGoogle Scholar
  26. 26.
    Bueno, P.M.S. Jino, M.: Identification of potentially infeasible program paths by monitoring the search for test data. In: Automated Software Engineering, Grenoble (2000)Google Scholar
  27. 27.
    Ayari, K., Bouktif, S., Antoniol, G.: Automatic mutation test input data generation via Ant colony. In: GECCO’07 Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (2007)Google Scholar
  28. 28.
    Wong, W.E., Horgan, J.R., London, S.: Effect of test set minimization on fault detection effectiveness. In: Proceedings of the 17th International Conference on Software Engineering (1995) Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Neha Prabhakar
    • 1
  • Abhishek Singhal
    • 1
  • Abhay Bansal
    • 1
  • Vasundhara Bhatia
    • 1
  1. 1.Department of CSE, ASETAmity UniversityNoidaIndia

Personalised recommendations