Optimizing for the number of tests generated in search based test data generation with an application to the oracle cost problem

Abstract

Previous approaches to search based test data generation tend to focus on coverage, rather than oracle cost. While there may be an aspiration that systems should have models, checkable specifications and/or contract driven development, this sadly remains an aspiration; in many real cases, system behaviour must be checked by a human. This painstaking checking process forms a significant cost, the oracle cost, which previous work on automated test data generation tends to overlook. One simple way to reduce oracle cost consists of reducing the number of tests generated. In this paper we introduce three algorithms which do this without compromising coverage achieved. We present the results of an empirical study of the effectiveness of the three algorithms on five benchmark programs containing non trivial search spaces for branch coverage. The results indicate that it is, indeed, possible to make reductions in the number of test cases produced by search based testing, without loss of coverage. © 2010 IEEE.