abstract = "Evolutionary algorithms have been successfully applied
in the area of software testing. However, previous
approaches in the area of object-oriented testing are
limited in terms of test case feasibility due to call
dependences and runtime exceptions. In this paper, we
present a search-based approach to automatically
generating test cases for object oriented software. It
relies on a tree-based representation of method call
sequences. Strongly-typed genetic programming is
employed to generate method call trees which respect
the call dependences among the methods. We apply a new
kind of distance-based fitness function that accounts
for runtime exceptions. In a case study, the approach
outperformed random testing in terms of achieved
coverage and it produced test cases achieving full
branch coverage for a test object that makes ample use
of explicit runtime exceptions.",
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.