Using genetic algorithms and coupling measures to devise optimal integration test orders

Lionel C. Briand, Jie Feng, Yvan Labiche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present here an improved strategy to devise optimal integration test orders in object-oriented systems. Our goal is to minimize the complexity of stubbing during integration testing as this has been shown to be a major source of expenditure. Our strategy to do so is based on the combined use of inter-class coupling measurement and genetic algorithms. The former is used to assess the complexity of stubs and the latter is used to minimize complex cost functions based on coupling measurement. Using a precisely defined procedure, we investigate this approach in a case study involving a real system. Results are very encouraging as the approach clearly helps obtaining systematic and optimal results.

Original languageEnglish
Title of host publicationProceedings of the 14th International Conference on Software Engineering and Knowledge Engineering, SEKE '02
Pages43-50
Number of pages8
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event14th International Conference on Software Engineering and Knowledge Engineering, SEKE '02 - Ischia, Italy
Duration: 15 Jul 200219 Jul 2002

Publication series

NameACM International Conference Proceeding Series
Volume27

Conference

Conference14th International Conference on Software Engineering and Knowledge Engineering, SEKE '02
Country/TerritoryItaly
CityIschia
Period15/07/0219/07/02

Keywords

  • genetic algorithms
  • integration order
  • integration testing
  • object-oriented software engineering

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