A Detailed Investigation of the Effectiveness of Whole Test Suite Generation

A common application of search-based software testing is to generate test
cases for all goals defined by a coverage criterion (e.g., lines, branches, mutants).
Rather than generating one test case at a time for each of these goals individually,
whole test suite generation optimizes entire test suites towards satisfying all goals
at the same time. There is evidence that the overall coverage achieved with this approach
is superior to that of targeting individual coverage goals. Nevertheless, there
remains some uncertainty on (a) whether the results generalize beyond branch coverage,
(b) whether the whole test suite approach might be inferior to a more focused
search for some particular coverage goals, and (c) whether generating whole test
suites could be optimized by only targeting coverage goals not already covered. In
this paper, we perform an in-depth analysis to study these questions. An empirical
study on 100 Java classes using three different coverage criteria reveals that indeed
there are some testing goals that are only covered by the traditional approach, although
their number is only very small in comparison with those which are exclusively
covered by the whole test suite approach. We find that keeping an archive of
already covered goal with corresponding tests and focusing the search on uncovered
goals overcomes this small drawback on larger classes, leading to an improved overall
effectiveness of whole test suite generation.