  Today, most automated test generators, such as search-based software testing
(SBST) techniques focus on achieving high code coverage. However, high code
coverage is not sufficient to maximise the number of bugs found, especially
when given a limited testing budget. In this paper, we propose an automated
test generation technique that is also guided by the estimated degree of
defectiveness of the source code. Parts of the code that are likely to be more
defective receive more testing budget than the less defective parts. To measure
the degree of defectiveness, we leverage Schwa, a notable defect prediction
technique.
  We implement our approach into EvoSuite, a state of the art SBST tool for
Java. Our experiments on the Defects4J benchmark demonstrate the improved
efficiency of defect prediction guided test generation and confirm our
hypothesis that spending more time budget on likely defective parts increases
the number of bugs found in the same time budget.
