Test Case Prioritization by Combining Mirror Adaptive Random Testing and Forgetting

This research examines test case prioritization methods that employ information from the previously selected test cases. Three methods were studied, namely Mirror Adaptive Random Testing, Consecutive Retention Forgetting, and the combination of Mirror Adaptive Random Testing and Forgetting. The next...

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Bibliographic Details
Published in:	2022 IEEE International Conference of Computer Science and Information Technology (ICOSNIKOM) pp. 1 - 5
Main Authors:	Sinaga, Arnaldo Marulitua, Yohana, Rosa Amelia B, Sijabat, Apriyanti, Manullang, Yohana Christina
Format:	Conference Proceeding
Language:	English
Published:	IEEE 19-10-2022
Subjects:	Complexity theory Computer science Costs Forgetting Information technology MART Mirrors Software algorithms Software testing Test Case Prioritization
Online Access:	Get full text
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Summary:	This research examines test case prioritization methods that employ information from the previously selected test cases. Three methods were studied, namely Mirror Adaptive Random Testing, Consecutive Retention Forgetting, and the combination of Mirror Adaptive Random Testing and Forgetting. The next method was proposed to combine the advantages of Mirror Adaptive Random Testing and Consecutive Retention Forgetting. The researchers conducted a series of experiment with Tobazone application as the program under test. All studied methods performance was compared with Random Testing as the basic testing method. Cost effectiveness of the studied methods were measured by using F-measure. The less F-measure the better. The result of the experiments showed that the all studied methods outperformed Random Testing significantly. It can reduce up to 47% of the cost of Random Testing. The new proposed method, the combination of Mirror Adaptive Random Testing and Forgetting, performed better than Forgetting in terms of effectiveness while Mirror Adaptive Random Testing was better in terms of efficiency (less complexity). Therefore, the proposed method can be considered as a good method for test case prioritization.
DOI:	10.1109/ICOSNIKOM56551.2022.10034907