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Improving regression testing transparency and efficiency with history-based prioritization – an industrial case study

Author

Summary, in English

Abstract—Background: History based regression testing was

proposed as a basis for automating regression test selection,

for the purpose of improving transparency and test efficiency,

at the function test level in a large scale software development

organization. Aim: The study aims at investigating the current

manual regression testing process as well as adopting, implementing

and evaluating the effect of the proposed method.

Method: A case study was launched including: identification of

important factors for prioritization and selection of test cases,

implementation of the method, and a quantitative and qualitative

evaluation. Results: 10 different factors, of which two are

history-based, are identified as important for selection. Most

of the information needed is available in the test management

and error reporting systems while some is embedded in the

process. Transparency is increased through a semi-automated

method. Our quantitative evaluation indicates a possibility to

improve efficiency, while the qualitative evaluation supports the

general principles of history-based testing but suggests changes

in implementation details.

Publishing year

2011

Language

English

Pages

367-376

Publication/Series

[Host publication title missing]

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Computer Science

Keywords

  • empirical evaluation
  • Keywords-regression testing
  • regression test selection
  • history-based prioritization
  • regression test prioritization
  • industrial case study
  • function testing

Conference name

IEEE Fourth International Conference on Software Testing, Verification and Validation (ICST), 2011

Conference date

2011-03-21 - 2011-03-25

Conference place

Berlin, Germany

Status

Published

Project

  • Embedded Applications Software Engineering

ISBN/ISSN/Other

  • ISBN: 978-1-61284-174-8