Model Driven Testing based on Functional Test Case Generation with Redundancy Check

Authors

  • Farooq A Dept. of Information Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune Deemed University, Pune, 411043, Maharashtra, India
  • Jadhav P Dept. of Information Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune Deemed University, Pune, 411043, Maharashtra, India
  • Joshi SD Dept. of Information Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune Deemed University, Pune, 411043, Maharashtra, India

DOI:

https://doi.org/10.26438/ijcse/v7i2.10161019

Keywords:

Software testing, test suite reduction, code coverage

Abstract

Software testing is a major component of software development lifecycle and it’s time-consuming. The testing used the particular time in testing is generally disturbed with generating the test cases and correctly testing them. Although some people apply k-means clustering algorithm to the test suite reduction, the algorithm is unstable and seldom considers the coverage rate of such test cases; as a result, it will waste various unnecessary testing times in redundant cases and always result in high cost. Model-based testing method is one of the testing categories in which the test cases derived from that the system describes efficient aspects of the system under test. When the model of the system is described explicitly, reversing system performed correctly, it can be used for the renewable artifact. For instance, the system can be used to generate an appropriate test set for the SUT. Such technique is called model-based testing (MBT).The different approaches are implemented and evaluated in order to determine its effectiveness in reducing the redundancy of test case generation. The purpose of this project is to generate the test cases, prioritize them.

References

[1] FENG LIU, JUN ZHANG, ER-ZHOU ZHU, ”TEST-SUITE REDUCTION BASED ON K-MEDOIDS CLUSTERING ALGORITHM”, CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY.

[2] KARTHEEK MUTHYALA,” A NOVEL APPROACH TO TEST SUITE REDUCTION USING DATA”, Indian Journal of Computer Science and Engineering (IJCSE), Computer Science and Information Systems, Birla Institute of Technology and Science, 2011.

[3] MOHAMMED AKOUR, IMAN AL JARRAH, AHMAD A. SAIFAN,”AN EFFICIENT APPROACH FOR TEST SUITE REDUCTIONUSING K-MEANS CLUSTERING”, Journal of Theoretical and Applied Information Technology,15th September 2018,Vol.96. No 17, 2018.

[4] Marwah Alian , Dima Suleiman , Adnan Shaout ,”Test Case Reduction Techniques – Survey”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 7, No. 5, 2016.

[5] Yulei Pang , Xiaozhen Xue , Akbar SiamiNamin ,”Identifying Effective Test Cases Through K-means Clustering for Enhancing Regression Testing”,2013 12th International Conference on Machine Learning and Applications.

[6] Yogesh Singh, Arvinder Kaur, Bharti Suri,” Test Case Prioritization using Ant Colony Optimization”, DOI: 10.1145/1811226.1811238, July 2010 Volume 35 Number 4 DOI: 10.1145.2010.

[7] M. LAKSHMI PRASAD1, M. KEERTHI2, K. SAI SRIKAR3, V. DIVYA4,”Generating Optimized Pair wise Test Cases by using K-Means Algorithm,”ISSN 2348–2370 Vol.09, Issue.05, April-2017.

[8]J.J. Gutiérrez, M.J. Escalona, M. Mejías,”A Model Driven Approach for Functional Test Cases”, Elsevier 12 August 2015.

[9] Mohamed El-Attar, Hamza Luqman, Peter Karpati, Guttorm Sindre,” Extending the UML State charts Notation to Model Security Aspects”, Member, IEEE, and Andreas L. Opdahl, Member, IEEE, Springer July 2015.

[10] Anjali Sharma and Maninder Singh, “Generation of Automated Test Cases Using UML Modeling”, International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 4, April - 2013 ISSN: 2278-0181.

Downloads

Published

2019-02-28
CITATION
DOI: 10.26438/ijcse/v7i2.10161019
Published: 2019-02-28

How to Cite

[1]
A. Farooq, P. Jadhav, and S. Joshi, “Model Driven Testing based on Functional Test Case Generation with Redundancy Check”, Int. J. Comp. Sci. Eng., vol. 7, no. 2, pp. 1016–1019, Feb. 2019.