Empirical evaluation of optimization algorithms when used in goal-oriented automated test data generation techniques
Software testing is an essential process in software development. Software testing is very costly, often consuming half the financial resources assigned to a project. The most laborious part of software testing is the generation of test-data. Currently, this process is principally a manual process. Hence, the automation of test-data generation can significantly cut the total cost of software testing and the software development cycle in general. A number of automated test-data generation approaches have already been explored. This paper highlights the goal-oriented approach as a promising approach to devise automated test-data generators. A range of optimization techniques can be used within these goal-oriented test-data generators, and their respective characteristics, when applied to these situations remain relatively unexplored. Therefore, in this paper, a comparative study about the effectiveness of the most commonly used optimization techniques is conducted.
test-data generation optimization techniques empirical software engineering empirical results