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Minimization of Test Suites for Fuzzy Object-Oriented Database

by Shweta Dwivedi, Santosh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 43
Year of Publication: 2018
Authors: Shweta Dwivedi, Santosh Kumar
10.5120/ijca2018915905

Shweta Dwivedi, Santosh Kumar . Minimization of Test Suites for Fuzzy Object-Oriented Database. International Journal of Computer Applications. 179, 43 ( May 2018), 10-15. DOI=10.5120/ijca2018915905

@article{ 10.5120/ijca2018915905,
author = { Shweta Dwivedi, Santosh Kumar },
title = { Minimization of Test Suites for Fuzzy Object-Oriented Database },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 179 },
number = { 43 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 10-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number43/29369-2018915905/ },
doi = { 10.5120/ijca2018915905 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:14.185915+05:30
%A Shweta Dwivedi
%A Santosh Kumar
%T Minimization of Test Suites for Fuzzy Object-Oriented Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 43
%P 10-15
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Test suite optimization is an effective method that is used to minimize or reduce the time and cost of testing. There are several researchers and software professionals have used this method or techniques to enhance the correctness and effectiveness of test suites/cases. These approaches optimize test suite for a single objective but fuzzy logic with certain algorithm is used to optimize the test cases/suites for multi objective selection processes. Therefore, in the present work an approach of optimization or minimization of test suites is proposed for the designed fuzzy object-oriented database and also applied this approach to reduce the complexity of the designed database. The main objective of our approach is to minimize and find the test suite that is best optimal for multi-objective testing.

References
  1. Bhasin H., Gupta S. and Kathuria M., “Regression Testing Using Fuzzy Logic”, International Journal of Computer Science and Information Technologies 2013; Vol. 4 Issue 2, pp. 378-380.
  2. Mudgal P.A., “A Proposed Model for Minimization of test Suite”, Journal of Nature Inspired Computing, 2013, Vol. 1, Issue 2, pp. 34-37.
  3. Alakeel M.A., “A Fuzzy Test Case Prioritization Technique for Regression Testing Programs with Assertions”, The Sixth International Conference on Advanced Engineering Computing and Application in Sciences 2012; 78-82.
  4. Haider AA, Nadeem A, Akram S, “Regression Test Suite Optimization Using Adaptive Neuro Fuzzy Inference System”, Frontiers of Information Technology 2016, pp. 52-56.
  5. Haider AA, Rafiq S, Nadeem A, “Test Suite Optimization Using Fuzzy Logic”, International Conference on Emerging Technologies, 2012, pp. 1-6.
  6. Shamshiri A., Rojas M.J., Fraser G. and McMinn P., “Random or Genetic Algorithm search for Object-Oriented Test Suite Generation”, Conference on Genetic and Evolutionary Computation 2015; 1367-1374.
  7. Qiu D, Li B, Ji S, Lenung H, “Rgeression Testing of Web Service: A Systematic Mapping Study”, ACM Computing Surveys 2015, Vol. 47, Issue 2.
  8. Kumar G., and Bhatia K.P., “Software Testing Optimization Through Test Suite Reduction Using Fuzzy Clustering”, Springer CSIT. 2013, Vol. 1, Issue 3, pp. 253-260.
  9. Usaola P.M., Mateo R.P. and Lamancha P.B., “Reduction of Test Suites Using Mutation”, Springer-Verlag Berlin Heidelberg 2012, Vol. 72, Issue 12, pp. 425-438.
  10. Singh S, Shree R, “A Combined Approach to Optimize the Test Suite Size in Regression Testing”, CSI Transaction on ICT, 2016, Vol. 4 Issue 2, pp. 73-78
  11. Asoudeh N. and Labiche Y., “A multi-Objective Genetic Algorithm for Generating Test Suites from Extended Finite State Machine”, International Symposium on Search Based Software Engineering 2013; pp. 288-293.
  12. Ma YX, Sheng KB, Ye GC, “Test-Suite Reduction Using Genetic Algorithm”, International Workshop on Advanced Parallel Processing Technologies 2005, pp. 253-262.
  13. Selva kumar S., Dinesh C.R.M. Dhinesh kumar C, and Ramraj N, “Reducing the Size of the Test Suite by Genetic Algorithm and Concept Analysis”, Recent Trends in Network and Communications; 153-161.
  14. Dinca L, “Multi-Objective Test Suite Optimization for Event-B Models”, International Conference on Informatics Engineering and Information Science 2011, pp. 551-565.
  15. Raamesh L, Uma VG, “Data Mining Based Optimization of test Cases to Enhance the Reliability of the Testing”, Advances in Computing and Information Technology; pp. 89-98.
  16. Patton R, “Software Testing”, Pearson Education 2001.
  17. Mondal K.S. and Tahbildar H., “Regression Test Cases Minimization for Object Oriented Programming using New Optimal Page Replacement Algorithm”, International Journal of Software Engineering and Its Applications 2014, Vol. 8, Issue 6, pp. 253-264.
  18. Subhashini B, JeyaMala D, “Reduction of Test Cases Using Clustering Technique”, International Journal of Innovative Research in Science, Engineering and Technology 2014, Vol. 3, Issue 3, pp. 1992-1996.
Index Terms

Computer Science
Information Sciences

Keywords

FOOD Test suites Test suites optimizations C-Means Clustering.

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