出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：We present a metaheuristic algorithm for testing software, especially web applications, that canbe modelled as a state transition diagram. We formulate the testing problem as an optimizationproblem and use a genetic algorithm to generate test cases as sequences of events. Thisalgorithm evolves solutions by maximizing a fitness function that is based on testing objectivessuch as the coverage of events, diversity of events, and continuity of events. The proposedapproach includes weights that can be assigned to events. These events would lead to importantfeatures or web pages in order to ensure that test cases will be generated to cover thesefeatures. The effectiveness of the genetic algorithm is compared with that of other algorithms,namely simulated annealing and a greedy algorithm. Our experimental results show that theproposed genetic algorithm demonstrates serious promise for testing state-based software,especially web applications.
关键词：Genetic Algorithm; Metaheuristics; Search Based Software Engineering; State-Based Testing;Testing Web Applications
