Enhancing the Performance of Coverage-Based Techniques in Test Case Prioritization

Authors(3) :-G. Bhavyasri, Prof. A. AnandaRao, Dr. P. Radhika Raju

A presented approach is based on coverage techniques using closed dependency structure. Test cases are grouped in clusters from functional dependency. Closed functional dependency structure is applied to arrange test case in each cluster, Test case prioritization is done from function-coverage information. Results demonstrate that, proposed method performs better when compared to code coverage technique and some other coverage techniques in test case prioritization. Moreover, current approach capitulate 97% of average percentage of fault detection (APFD) and coefficient of determination in correlation as 0.8363, which enhances the performance of coverage-based techniques.

Authors and Affiliations

G. Bhavyasri
M.Tech Scholar, Department of CSE, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India
Prof. A. AnandaRao
Professor, Department of CSE, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India
Dr. P. Radhika Raju
Ad-hoc Assistant Professor, Department of CSE, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India

Regression Testing, Dependency Structures, Clustered Technique, Test Case Prioritization, Function Coverage Techniques.

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-09-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 468-473
Manuscript Number : CSEIT1725102
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Bhavyasri, Prof. A. AnandaRao, Dr. P. Radhika Raju, "Enhancing the Performance of Coverage-Based Techniques in Test Case Prioritization", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.468-473, September-October-2017.
Journal URL : http://ijsrcseit.com/CSEIT1725102

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