Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/21629
Title: Software Engineering Solutions for Improving the Regression Testing Methods in Scientific Applications Development
Authors: Koteska, Bojana 
Pejov, LJupcho 
Mishev, Anastas 
Keywords: Regression testing
Scientific application
Software quality
Issue Date: 2013
Publisher: CEUR-WS.org
Source: Bojana Koteska, Ljupco Pejov, and Anastas Mishev. “Software Engineering Solutions for Improving the Regression Testing Methods in Scientific Applications Development”. In: Proceedings of the 2nd Workshop on Software Quality Analysis, Monitoring, Improve- ment, and Applications, SQAMIA 2013. Vol. 1053. Novi Sad, Serbia: Faculty of Sciences, University of Novi Sad, Serbia, 2013, pp. 53–61. ISBN: 978-86-7031-269-2.
Conference: 2nd Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2013.
Abstract: The aim of this paper is to improve the testing process of scientific applications by proposing some software engineering solutions for regression testing. Given the fact that changes are a common part of the development of scientific applications the need for regression testing is essential. Concerning to improve the methods of regression testing the relationship between requirements and test case selection for regression testing is included as a relevant for improving the overall quality of the testing process. Special emphasis is given on the requirements’ changes during the application development process and their impact on test case modifications. In addition, we also state the reasons for the implementation and the importance of the regression testing as a part of the verification process of scientific applications. In order to get more relevant results we made an interview with a scientist (chemist) about the regression testing practices in scientific applications. The conclusions and recommendations in this paper are based on the analysis of the results of a survey conducted among scientists in the HP-SEE project and the answers of the interview questions.
URI: http://hdl.handle.net/20.500.12188/21629
ISBN: 978-86-7031-269-2
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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