We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing

by Dr. Arvinder Kaur, Divya Bhatt
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 10
Year of Publication: 2011
Authors: Dr. Arvinder Kaur, Divya Bhatt
10.5120/3336-4589

Dr. Arvinder Kaur, Divya Bhatt . Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing. International Journal of Computer Applications. 27, 10 ( August 2011), 27-34. DOI=10.5120/3336-4589

@article{ 10.5120/3336-4589,
author = { Dr. Arvinder Kaur, Divya Bhatt },
title = { Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 10 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number10/3336-4589/ },
doi = { 10.5120/3336-4589 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:25.497924+05:30
%A Dr. Arvinder Kaur
%A Divya Bhatt
%T Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 10
%P 27-34
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software Testing is continuous process of development and maintenance in life of software. In maintenance phase, regression testing gets exercisedwith additional resources/time for performance. The prioritization of test cases helps to reduce the cost-time of regression testing. Hence, completing Regression Testing effectively and on schedule is challenge for software tester. In this research paper, the Particle Swarm Optimization (PSO) technology has been studied and used with the blend of Genetic Algorithm (GA) and the hybrid prioritized algorithm has been proposed. The Particle Swarm Optimization is an optimization algorithm based on heuristic search which can be used to solve time-constraint environment of Test Case Prioritization and the concept of Genetic Algorithm will further help in diversifying the solution within whole search space. For finding the effectiveness of hybrid prioritization algorithm: the efficiency %, saving %, reduction % and APFD/APCC has been calculated.

References
  1. Alspaughy, S., Walcotty,K. R., Belanichz, M., Kapfhammerz,G. M., Lou Soffa,M.,2007 Efficient Time-Aware Prioritization with Knapsack Solvers, Proceedings of the ASE 2007 Atlanta, Georgia, November 2007.
  2. Garey,M.R., Johnson,D.S., 1979, Computers and Intractability, A Guide to the Theory of NP- Completeness, W. H. Freeman and Company, New York.
  3. Liang,Y, Liu,L.,Wang,D.,Wu, R., 2010,Optimizing Particle Swarm Optimization to Solve Knapsack Problem, ICICA, CICIS, Vol.105, Springer, Berlin, pp.: 437-443.
  4. Ezziane,Z., 2002 Solving the 0/1 knapsack problem using an adaptive genetic algorithm, Analysis and Manufacturing (AIEDAM), Vol.16(1), Jan-2010 pp.: 23-30.
  5. Premalatha,K., Natarajan, A.M.,2009Hybrid PSO and GA for Global Maximization,International Journal of Open Problems in Computer Science and Mathematics, Vol. 2, No. 4., pp. 597-608.
  6. Eberhart, R.C., Kennedy,J.,1995 A New Optimizer Using Particles Swarm Theory,IEEE Service Center, Piscataway, NJ, Nagoya, Japan, pp.:39-43.
  7. Srivastava, P. R., Kim,T., 2009 Application of Genetic Algorithm in Software Testing, International Journal of Software Engineering and Its Applications Vol. 3(4), pp.: 87-96.
  8. Lope, H.S.,Coelho, L.S., 2005 Particle Swarm Optimization with fast local search for the blind traveling salesman problem, Proceedings of Fifth International Conference on hybrid intelligent systems (HIS’05), Brazil, pp.: 245-250.
  9. Yoshikawa, M.,Nishimura, H., Terai, H., 2010 A New Genetic Coding for Job Shop Scheduling Problem Considering Geno type and Pheno type, Proceeding of the 4th WSEAS International Conference on Computer Engineering and Applications, Harvard University, Cambridge, SEAS Press, pp.: 59-62.
  10. Walcott, K. R.,Kapfhammer, G. M., Soffa, M. L., Roos, R. S., 2006 Time-aware test suite prioritization, Proceedings of International Symposium on Software Testing and Analysis, USA, pp. 1-19, July 2006.
  11. ASKARUNISA, A., SHANMUGAPRIYA, L., RAMARAJ, N., 2009 Cost and Coverage Metrics for Measuring the Effectiveness of Test Case Prioritization Techniques, pp.: 1-10.
  12. Wong, W. E., Horgan, J. R., London, S. and Agrawal, H., 1997, A study of effective regression testing in practice, In Proceedings of the 8th IEEE International Symposium on Software Reliability Engineering (ISSRE' 97), November 1997 , pp.: 264-274.
  13. Singh, Y., Kaur,A., Suri, B., 2006 A New Technique for Version – Specific Test Case Selection and Prioritization for Regression Testing, Journal of the Computer Society of India, Vol.36(4), pp.: 23-32.
  14. Aggrawal, K. K., Singh, Y., Kaur, A., 2004 Code coverage based technique for prioritizing test cases for regression testing, ACM SIGSOFT Software Engineering Notes , Vol.-29(5) pp.:1-4.
  15. Singh,Y., Kaur,A., and Suri,B., 2010 AHybrid Approach for Regression Testing in Intraprocedural Programs, JIPS, Vol.6 (1), pp.:21-32, March 2010.
  16. Singh,Y., Kaur,A., and Suri,B., 2010, “Test Case Prioritization Using Ant Colony optimization”, Association in Computing Machinery,ACM SIGSOFT Software Engineering Notes, USA, July 2010, pp.: 1-7.
  17. Hla, K. H.S., Choi, Y., Park, J. S., 2008 Applying Particle Swarm Optimization to Prioritizing Test Cases for Embedded Real Time Software Retesting, Proceedings of the IEEE 8th International Conference on Computer and Information Technology Workshops, pp.: 527-532.
  18. Aggrawal, K. K., Singh, Y., Kaur, A., 2004 Code Coverage Based Technique for prioritizing Test Cases for Regression Testing, ACM SIGSOFT Software Engineering Notes, Vol.29(5), September 2004.
  19. 19 Fischer, K., Raji, F.,Chruscicki, A., 1981 A methodology for retesting modified software, In Proc. of the Nat'l. Tele. Conf. B-6-3, Nov. 1981, pp. 1-6.
  20. Mehta, A., Heineman,G.T., 2000 Evolving Legacy Systems Features for Regression Test Cases and Components, Worcester Ploy technique Institute, MA, pp.: 1-11.
  21. S. Yoo, M. Harman and S. Ur, “ Highly Scalable Multi Objective Test Suite Minimization Using Graphic Card”, Department of Computer Science, University College of London, UK, 2007, pp.: 1-26.
  22. Harman, M., Mansouri, A., 2010 Search Based Software Engineering: Introduction to special issue of IEEE Transactions on Software Engineering, IEEE Transactions, Vol-6, No-4, Nov-2010, pp.: 737-741.
  23. M. Harman, “Making the case for MORTO: Multi objective Regression Test Optimization”, University College of London, CREST center London, pp.:1-4
  24. 24Li,Z., Harman, M. and Hierons, R. M., 2007 Search algorithms for regression test case prioritization, IEEE Trans. On Software Engineering, Vol.-33, No.-4, April 2007, pp.: 76-89.
  25. Liu, H., Sun, S., Abraham, A.,2006 Particle swarm approach to scheduling work-flow applications in distributed data- intensive computing environments, Proceedings of Sixth International Conference on In Intelligent Systems Design and Applications, ISDA’06, pp.: 661–666.
  26. Zhao, F., Zhang, Q., Yang, Y., 2006 An improved particle swarm optimization based approach for production scheduling problems, in: Proceedings of the IEEE International Conference on Mechatronics and Automation, pp.:2279–2283.
  27. Kong,X., Sun, J., Xu,W., 2006 Particle swarm algorithm for tasks scheduling in distributed heterogeneous system, in Proceedings of Sixth International Conference on ISDA’06, pp.: 690–695.
  28. Laskari,E.C., Meletiou, G.C., Vrahatis, M.N., 2006 Utilizing evolutionary computation methods for the design of s-boxes, in Proceedings of International Conference on CIS-2006, pp.: 1299–1302.
  29. Zhi,X.H., Xing, X.L., Wang, Q.X., Zhang, L.H., Yang, X.W., Zhou, C.G., Liang, Y.C., 2004 A discrete PSO method for generalized TSP problem, in: Proceedings of International Conference In Machine Learning and Cybernetics, (4), pp.: 2378–2383.
  30. Liu,D.S., Tan,K.C., Goh,C.K., Ho, W.K., 2006 On solving multi objective bin packing problems using particle swarm optimization, in: Proceedings of IEEE Congress on Evolutionary Computation, CEC2006, pp.: 2095–2102.
  31. Hou,Y.,Zhao, C., Liao,Y., 2006 A new method of test generation for sequential circuits, in Proceedings, 2006 International Conference on Communications, Circuits and Systems, pp.: 2181–2185.
  32. Sheta, A., 2006 Reliability growth modeling for software fault detection using particle swarm optimization, Proceedings of IEEE Congress on Evolutionary Computation, CEC2006, pp.: 3071–3078.
  33. Krishnamoorthi, R., Mary, S.A., 2009Regression Test Suite Prioritization using Genetic Algorithms, International Journal of Hybrid Information Technology, Vol.2(3),, July 2009, pp.: 35-52.
  34. Kamble, A., 2010 Incremental Clustering in Data Mining using Genetic Algorithm, International Journal of Computer Theory and Engineering, Vol.2(3), , June 2010, pp.: 1793-8201.
  35. Bergmann,K. P., Scheidler,R., Jacob, C., 2008Cryptanalysis using genetic algorithms, in 10th annual conference on Genetic and evolutionary computation, ACM New York, NY, USA, pp.: 1099-1100.
  36. Krishna,K. S. R.,Reddy, A. G., Prasad, M.N.G., Rao, K.C., Madhavi, M., 2010 Genetic Algorithm Processor for Image Noise Filtering Using Evolvable Hardware, International Journal of Image Processing, Vol.4(3), pp.: 240-250.
  37. Li,M., Zhang,Y., Jiang, W., Xie,J., Coll,Z., 2009 A Particle Swarm Optimization Algorithm with Crossover for Resource Constrained Project Scheduling Problem, Proceedings of IITA SSME’09, pp.: 69-72.
  38. Rothermel,G.,Harold, M. J., 1997 A Safe, Efficient Regression Test Selection Technique,ACM Transaction on Software Engineering and Methodology, Vol.6 (2),, April 1997, pp.: 173-210.
  39. Aggarwal,K.K.,Singh,Y., 2001 Software Engineering, New Age International (P) Ltd.; Publishers, 4835/24, Ansari Road, Daryaganj, New Delhi.
Index Terms

Computer Science
Information Sciences

Keywords

Regression Testing Particle Swarm Optimization Genetic Algorithms

Powered by PhDFocusTM