Automatic Test-Data Generation: An Immunological Approach

In previous research, we presented an approach to automatically generate test-data for object-oriented software exploiting a genetic algorithm (GA) to achieve high levels of data-flow coverage. The experimental results from testing six Java classes helped us identify a number of problematic test targets, and suggest that in the future full data-flow coverage with a reasonable computational cost may be possible if we overcome these obstacles. To this end, the investigation of artificial immune system (AIS) algorithms was chosen. This paper provides a brief summary of our previous work and an introduction to both human and artificial immune system. We then suggest a framework for the application of AIS algorithms to the problem of automated testing, followed by some thoughts on why and how these algorithms can be beneficial in our effort to improve the performance of our previously implemented GA. Finally, our preliminary results from a proof-of-concept implementation are presented.