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.
|Title of host publication||GECCO 2007|
|Subtitle of host publication||genetic and evolutionary computation conference proceedings|
|Place of Publication||New York|
|Number of pages||1|
|Publication status||Published - 2007|
|Event||Annual Conference of Genetic and Evolutionary Computation Conference - London, United Kingdom|
Duration: 7 Jul 2007 → 11 Jul 2007
|Conference||Annual Conference of Genetic and Evolutionary Computation Conference|
|Period||7/07/07 → 11/07/07|
- data-flow coverage
- evolutionary algorithms
Liaskos, K., Roper, M., & Wood, M. (2007). Investigating data-flow coverage of classes using evolutionary algorithms. In GECCO 2007: genetic and evolutionary computation conference proceedings (pp. 1140-1140).