Software testing is one of the most arduous and challenging phase which is to be implemented with the intention of finding faults with the execution of minimum number of test cases to increase the overall quality of the product at the time of delivery or during maintenance phase. With the ever increasing demand of web applications and to meet never ending customer expectations, updations are to incorporate which will be validated through testing process. The structure of the web applications (dynamic website) can be modeled using weighted directed graph which consists of numerous paths starting from homepage (index page) of the website. For thorough testing of the website each and every path of the graph should be tested but due to various constraints like time, money and human resources it becomes very much impractical. This scenario ultimately gives rise to the motivation for the development of technique which reduces the number of paths to be tested so that tester community can test only these numbers of path instead of all possible paths so that satisfactory number of faults can be exposed.
In this proposed approach assignment of weights on the edges of the directed graph takes place on the basis of the organization of the website, changes in the structure of the website at page level, experience of the coder and the behaviour of the users who have visited the website earlier. The most fault prone paths are identified using random, greedy, Ant Colony Optimization (ACO) and Artificial Bee Colony Optimization (ABCO) algorithms. Two small size websites and one company’s website, and their two versions, were considered for experimentation. Results obtained through ACO and ABCO are promising in nature. This approach will support testing process to be completed in time and delivery of the updated version within given hard deadlines.

Regression testing is a process that executes subset of tests that have already been conducted to ensure that changes have not propagated unintended side effects. Test case prioritization aims at reordering the regression test suit based on certain criteria, so that the test cases with higher priority can be executed first rather than those with lower priority. In this paper, a new approach for test case prioritization has been proposed which is based on a module-coupling effect that considers the module-coupling value for the purpose of prioritizing the modules in the software so that critical modules can be identified which in turn will find the prioritized set of test cases. In this way there will be high percentage of detecting critical errors that have been propagated to other modules due to any change in a module. The proposed approach has been evaluated with a case study of software consisting of ten modules.