Abstract
Regression testing is considered to be one of the most costly, time-taking, and important activity which is performed in an environment with a number of certain restrictions for ensuring the validity of a modified software. Therefore, it becomes necessary to pick the sequence of test cases which is correct as well as it should have the ability to traverse all the faults taking minimum execution time. Prioritizing the test cases helps to achieve performance requirements in which important test cases are executed before than those having lower degree of importance. Studies have shown that prioritization approaches based on test factors like Importance, Volatility, Complexity, Fault Rate, Time, Coverage have good results and also the approaches based on intelligent techniques like Ant Colony, genetic algorithms, have been very promising. Hence, this paper presents a hybrid of these two approaches which first generates the test cases based on the priorities, which are assigned using test factors, and then, the best sequence having least execution time and highest fault rate is calculated by the Ant Colony Optimization algorithm.
This is a preview of subscription content, log in via an institution to check access.
References
L. Zhang, S. S. Hou, C. Guo, T. Xie and H. Mei “Time Aware Test-Case Prioritization using Integer Linear Programming”, ISSTA’09, Chicago, Illinois, USA, Jul 2009.
Mathur, A. P.: Foundations of Software Testing. Pearson (2008).
Myers, G.: The Art of Software Testing. John Wiley & Sons, Inc, 2nd Edition (2004).
B. Boehm and L. Huang, “Value-Based Software Engineering: A Case Study,” IEEE Computer, vol. 36, pp. 33–41, Mar 2003.
Harman, M., Jones, B. F.: Search-based software engineering. Information and Software Technology, vol. 43, n. 14, pp. 833–839 (2001).
Maia, C. L. B., Carmo, R. A. F., Freitas, F. G., Campos, G. A. L., Souza, J. T.: Automated Test Case Prioritization with Reactive GRASP. Advances in Software Engineering (2010).
Walcott, K. R., Soffa, M. L., Kapfhammer, G. M., Roos, R. S.: Time-Aware Test Suite Prioritization. In: Proceedings of the International Symposium on Software Testing and Analysis, pp. 1–12 (2006).
Mansour, N., Bahsoon, R., Baradhi, G.: Empirical Comparison of Regression Test Selection Algorithms. Journal of Systems and Software, vol. 57, n. 1, pp. 79–90, Elsevier (2001).
Li, Z., Harman, M., Hierons, R. M.: Search Algorithms for Regression Test Case Prioritization. IEEE Transactions on Software Engineering, vol. 33, n. 4, pp. 225–237 (2007).
Singh, Y., Kaur, A., Suri, B.: Test case prioritization using Ant Colony Optimization. ACM SIGSOFT Software Engineering Notes, vol. 35, n. 4, pp. 1–7 (2010).
Suri, B., Singhal, S.: Implementing Ant Colony Optimization for Test Case Selection and Prioritization. International Journal on Computer Science and Engineering, vol. 3, n. 5, pp. 1924–1932 (2011).
Dorigo, M., Stutzle, T.: The Ant Colony Optimization metaheuristic: Algorithms, applications, and advances. Handbook of Metaheuristics. Springer, pp. 250–285 (2003).
M. Fayoumi, P. Mahanti and S. Banerjee: OptiTest: “Optimizing Test Case Using Hybrid Intelligence” World Congress on Engineering 2007.
N S. Mirarab and L.Tahvildari “An Empirical Study on Bayesian Network-based Approach for Test Case Prioritization” Int. Conf. on Software Testing, Verification, and Validation 2008.
K. H. S Hla, Y. Choi and J. S. Park “Applying Particle Swarm Optimization to Prioritizing Test Cases for Embedded Real Time Software Retesting”, 8th IEEE Int. Conf. on Computer and Information Technology Workshops 2008.
F. Moisiadis, “Prioritising Use Cases and Scenarios,” 37th International Conference on Technology of OO Languages and Systems, Sydney, NSW, 2000, pp. 108–119.
J. Karlsson and K. Ryan, “A Cost-Value Approach for Prioritizing Requirements,” IEEE Software, vol. 14, no.5, pp. 67–74, Sep-Oct 1997.
J. C. Munson and S. Elbaum, “Software reliability as a function of user execution patterns and practice,” 32nd Annual Hawaii International Conference of System Sciences, Maui, HI, 1999, pp. 255–285.
J. Musa, Software Reliability Engineering. New York, NY: McGraw-Hill, 1999.
Y. K. Malaiya and J. Denton, “Requirements volatility and defect density,” 10th Intl’ Symposium on Software Reliability Engineering, Boca Ratan, Florida, November 1999, pp. 285–298.
G. Mogyorodi, “Requirements-Based Testing: An Overview,” 39th International Conference and Exhibition on Technology of Object-Oriented Languages and Systems, Santa Barbara, California, August 2001, pp. 286–295.
Computer, vol.29, no. 6 C. Jones, “Software Challenges: Strategies forManaging Requirements Creep,” IEEE, pp. 92–94, June 1996.
J. O’Neal and D. Carver, “Analyzing the Impact of Changing Requirements,” IEEE International Conference on Software Maintenance, Los Alamitos, California, 2001, pp. 190–195.
S. Amland, “Risk Based Testing and Metrics,” 5th International Conference EuroSTAR’99, Barcelona, Spain, 1999, pp. 1–20.
F. Shull, V. Basili, B. Boehm, W. Brown, P. Costa, M. Lindvall, D. Port, I. Rus, R. Tesoriero, and M. Zelkowitz, “What We Learned about Fighting Defects,” IEEE Symposium on Software Metrics, Ottawa, Canada, June 2002, pp. 249–258.
Sheikh Fahad Ahmad, Mohd. Rizwan Beg, Mohd. Haleem “Test Driven Development with Continuous Integration: A Literature Review”, International Journal of Computer Applications Technology and Research (IJCATR).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ahmad, S.F., Singh, D.K., Suman, P. (2018). Prioritization for Regression Testing Using Ant Colony Optimization Based on Test Factors. In: Singh, R., Choudhury, S., Gehlot, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-5903-2_142
Download citation
DOI: https://doi.org/10.1007/978-981-10-5903-2_142
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5902-5
Online ISBN: 978-981-10-5903-2
eBook Packages: EngineeringEngineering (R0)