Investigating data-flow coverage of classes using evolutionary algorithms

K. Liaskos, M. Roper, M. Wood

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

21 Citations (Scopus)
78 Downloads (Pure)


It is not unusual for a software development organization to expend 40% of total project effort on testing, which call be a very laborious and time-consuming process. Therefore, there is a big necessity for test automation. This paper describes an approach to automatically generate test-data for 00 software exploiting a Genetic Algorithm (GA) to achieve high levels of data-flow (d-u) coverage. A proof-of-concept tool is presented. The experimental results from testing six Java classes helped us identify three categories of problematic test targets, and suggest that in the future full d-u coverage with a reasonable computational cost may be possible if we overcome these obstacles.
Original languageEnglish
Title of host publicationGECCO 2007
Subtitle of host publicationgenetic and evolutionary computation conference proceedings
Place of PublicationNew York
Number of pages1
Publication statusPublished - 2007
EventAnnual Conference of Genetic and Evolutionary Computation Conference - London, United Kingdom
Duration: 7 Jul 200711 Jul 2007


ConferenceAnnual Conference of Genetic and Evolutionary Computation Conference
Country/TerritoryUnited Kingdom


  • data-flow coverage
  • classes
  • evolutionary algorithms
  • investigation


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