Investigating data-flow coverage of classes using evolutionary algorithms

Authors:
Konstantinos Liaskos;Marc Roper;Murray Wood
Affiliations:
University of Strathclyde, Glasgow, United Kingdom;University of Strathclyde, Glasgow, United Kingdom;University of Strathclyde, Glasgow, United Kingdom
Venue:
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Year:
2007

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Abstract

It is not unusual for a software development organization to expend 40% of total project effort on testing, which can 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 OO 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.