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Optimization of Test Case Generation using Genetic Algorithm (GA)

by Ahmed Mateen, Marriam Nazir, Salman Afsar Awan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 151 - Number 7
Year of Publication: 2016
Authors: Ahmed Mateen, Marriam Nazir, Salman Afsar Awan
10.5120/ijca2016911703

Ahmed Mateen, Marriam Nazir, Salman Afsar Awan . Optimization of Test Case Generation using Genetic Algorithm (GA). International Journal of Computer Applications. 151, 7 ( Oct 2016), 6-14. DOI=10.5120/ijca2016911703

@article{ 10.5120/ijca2016911703,
author = { Ahmed Mateen, Marriam Nazir, Salman Afsar Awan },
title = { Optimization of Test Case Generation using Genetic Algorithm (GA) },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 151 },
number = { 7 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 6-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume151/number7/26243-2016911703/ },
doi = { 10.5120/ijca2016911703 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:56:27.136859+05:30
%A Ahmed Mateen
%A Marriam Nazir
%A Salman Afsar Awan
%T Optimization of Test Case Generation using Genetic Algorithm (GA)
%J International Journal of Computer Applications
%@ 0975-8887
%V 151
%N 7
%P 6-14
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Testing provides means pertaining to assuring software performance. The total aim of software industry is actually to make a certain start associated with high quality software for the end user. However, associated with software testing has quite a few underlying concerns, which are very important and need to pay attention on these issues. These issues are effectively generating, prioritization of test cases, etc. These issues can be overcome by paying attention and focus. Solitary of the greatest Problems in the software testing area is usually how to acquire a great proper set associated with cases to confirm software. Some other strategies and also methodologies are proposed pertaining to shipping care of most of these issues. Genetic Algorithm (GA) belongs to evolutionary algorithms. Evolutionary algorithms have a significant role in the automatic test generation and many researchers are focusing on it. In this study explored software testing related issues by using the GA approach. In addition to right after applying some analysis, better solution produced, that is feasible and reliable. The particular research presents the implementation of GAs because of its generation of optimized test cases. Along these lines, this paper gives proficient system for the optimization of test case generation using genetic algorithm.

References
  1. Ali, B. M. Y. and Benmaiza, F., 2012. Generating Test Case for Object-Oriented Software Using Genetic Algorithm and Mutation Testing Method. International Journal of Applied Metaheuristic Computing, 3: 15–23.
  2. Athar, M. and Ahmad, I., 2014. Maximize the Code Coverage for Test Suit by Genetic Algorithm. International Journal of Computer Science and Information Technologies, 5(1): 431–435.
  3. Garg, R., and Mittal, S., 2014. Optimization by Genetic Algorithm. International Journal of Advanced Research in Computer Science and Software Engineering, 4(4): 587–589.
  4. Kaur, R. and Dhanda, S. K., 2013. Generation of Test Data Using Genetic Algorithm. International Journal of Engineering Research and Applications, 3(5): 573–574.
  5. Khan, R., M. Amjad and Pandey, D., 2014. Automated Test Case Generation using Nature Inspired Meta Heuristics- Genetic Algorithm. International Journal of Application or Innovation in Engineering & Management, 3(11): 7–9.
  6. Malhotra, R. and Bharadwaj, A., 2012. Test case priortization using genetic algorithm. International Journal of Computer Science and Informatics, 3: 63–66.
  7. Mondal, K. and Tahbildar, S. H., 2013. Automated Test Data Generation Using Fuzzy Logic-Genetic Algorithm Hybridization System for Class Testing Of Object Oriented Programming. International Journal of Soft Computing and Engineering, 3(5): 40–49.
  8. Sabharwal, S., Sibal R., and Sharma, C., 2011. Applying Genetic Algorithm for Prioritization of Test Case Scenarios Derived from UML Diagrams. International Journal of Computer Science, 8(3): 433-444.
  9. Saini, P. and Tyagi, S., 2014. Test Data Generation for Basis Path Testing Using Genetic Algorithm and Clonal Selection Algorithm. International Journal of Science and Research, 3(6): 2012–2015.
  10. Sharma, K. A., 2013. Optimized Test Case Generation Using Genetic Algorithm. International Journal of Computing and Business Research, 4(3): 4–7.
  11. Singh, A., Garg, N., and Saini, T., 2014. A hybrid Approach of Genetic Algorithm and Particle Swarm Technique to Software Test Case Generation. International Journal of Innovations in Engineering and Technology, 3(4): 208–214.
  12. Singhal, A., Chandna, S., and Bansal, A., 2012. Optimization of Test Cases Using Genetic Algorithm. International Journal of Emerging Technology and Advanced Engineering, 2(3): 367–369.
  13. Sumalatha, V. M., and Raju, G. S. V. P., 2013. Object Oriented Test Case Generation Technique using Genetic Algorithms. International Journal of Computer Applications, 61(20): 20–26.
  14. Tripathy, P. and Kanhar, S. D., 2013. Optimization of Software Testing for Discrete Tes tsuite using Genetic Algorithm and Sampling Technique. International Journal of Computer Applications, 63(7): 1–5.
  15. Varshney, S. and Mehrotra, M., 2014. Automated Software Test Data Generation for Data Flow Dependencies using Genetic Algorithm. International Journal of Advanced Research in Computer Science and Software Engineering, 4(2): 472–479.
Index Terms

Computer Science
Information Sciences

Keywords

Optimization Genetic Algorithm Test case Generation Design Testing.

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