Created by W.Langdon from gp-bibliography.bib Revision:1.8081
Genetic algorithms have already been used to tackle typical testing problems with success, but the use of genetic programming applied to automatic test case generation is relatively new and promising. This master thesis shows how genetic algorithms combined with different types of software analysis can create new unit tests with a high amount of program coverage. Together with static analysis, the genetic algorithm is able to generate tests for more real world programs in a shorter amount of time. This new approach is implemented in a prototype tool called EvoTest?. With this tool I demonstrate the coverage obtained for small programs and some larger real world programs.",
supervisor: Hans-Gerhard Gross (TUDelft)
Georgia Institute of Technology, Alex Orso, Jim Clause.
SERG The Software Engineering Research Group http://swerl.tudelft.nl/bin/view/Main/SoftwareEngineeringResearchGroup",
Genetic Programming entries for Arjan Seesing