This paper is published in Volume-4, Issue-3, 2018
Area
Software Engineering
Author
Priya Gupta, Dr. Anup Kumar Keshri
Org/Univ
Birla Institute of Technology, Ranchi, Jharkhand, India
Keywords
Forking, Test flakiness, Speed off, Ant colony optimization, Sequential testing, Parallel testing
Citations
IEEE
Priya Gupta, Dr. Anup Kumar Keshri. To study the impact and usage of test parallelization, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Priya Gupta, Dr. Anup Kumar Keshri (2018). To study the impact and usage of test parallelization. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.
MLA
Priya Gupta, Dr. Anup Kumar Keshri. "To study the impact and usage of test parallelization." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.
Priya Gupta, Dr. Anup Kumar Keshri. To study the impact and usage of test parallelization, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Priya Gupta, Dr. Anup Kumar Keshri (2018). To study the impact and usage of test parallelization. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.
MLA
Priya Gupta, Dr. Anup Kumar Keshri. "To study the impact and usage of test parallelization." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.
Abstract
The number of test cases required to ensure the quality of a software system grows hand in-hand with its complex and henceforth the total test execution time increases proportionally. Traditionally test cases are executed sequentially which takes much time. Thus parallel test execution appeared to be an appealing option to cut over the test execution time .This paper presents our findings on different techniques for test parallelization and its impact with respect to time and test flakiness. Test flakiness is the tests that fail randomly. We have applied the different techniques on a java project containing 623 test cases and observed the effect.Based on the result we have tried to conclude the optimal technique for test parallelization.
