Test Case Generation Using Progressively Refined Genetic Algorithm for Ajax Web Application Testing

Background: The real strengths of AJAX technology are that AJAX web application is fit for the heterogeneous and autonomous environment. On the other hand, AJAX poses new challenges and difficulties for web application maintenance, evolution, and testing. Therefore, the prime aim of this research work is to present a testing environment for an AJAX web application testing to prevent web application functionalities from failure/ fault. Methods: In this research work, Ajax testing is directed toward revealing faults related to incorrect manipulation of the DOM. Initial impetus has been made to model the dynamic behavior of web application with the help of user session based state machine. User session-based state machine extracts states, transitions and DOM change behavior of objects in a specific user session performed on the web application. Further, the Progressively Refined Genetic Algorithm (PRGA) is used to generate test cases of dynamic functionality of the chosen AJAX web application under test with the help of generated user session based state machine. Results: In order to validate the effectiveness of PRGA in revealing faults, faults have been injected in AJAX web application and efficiency of PRGA approach is validated corresponding to faults revealing capability. PRGA is applied to detect faults in all required test case to improve effectiveness and results have been compared with respect to the traditional genetic algorithm for test case generation. Conclusion: The proposed PRGA is able to generate the reduced test case that can cover test requirements in reduced search time.