Dynamic Test Case Prioritization in Industrial Test Result Datasets
Year of publication
2024
Authors
Alina Torbunova; Per Erik Strandberg; Ivan Porres
Abstract
Regression testing in software development checks if new software features affect existing ones. Regression testing is a key task in<br/>continuous development and integration, where software is built in small increments and new features are integrated as soon as<br/>possible. It is therefore important that developers are notified about possible faults quickly. In this article, we propose a test case prioritization schema that combines the use of a static and a dynamic prioritization algorithm. The dynamic prioritization algorithm rearranges the order of execution of tests on the fly, while the tests are being executed. We propose to use a conditional probability<br/>dynamic algorithm for this. We evaluate our solution on three industrial datasets and utilize Average Percentage of Fault Detection<br/>for that. The main findings are that our dynamic prioritization algorithm can: a) be applied with any static algorithm that assigns<br/>a priority score to each test case b) can improve the performance of the static algorithm if there are failure correlations between test<br/>cases c) can also reduce the performance of the static algorithm, but only when the static scheduling is performed at a near optimal<br/>level.<br/>
Show moreOrganizations and authors
Publication type
Publication format
Article
Parent publication type
Conference
Article type
Other article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A4 Article in conference proceedingsPublication channel information
Journal/Series
Proceedings - 2024 IEEE/ACM International Conference on Automation of Software Test, AST 2024
Parent publication name
Proceedings - 2024 IEEE/ACM International Conference on Automation of Software Test, AST 2024
Pages
154-158
ISBN
Publication forum
Publication forum level
1
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Partially open publication channel
Self-archived
Yes
Other information
Fields of science
Computer and information sciences
Keywords
[object Object],[object Object],[object Object]
Internationality of the publisher
International
Language
English
International co-publication
Yes
Co-publication with a company
Yes
DOI
10.1145/3644032.3644452
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes