A Regression Test Case Prioritization Technique for Web Application Using User Session Data

We propose a novel regression test case prioritization technique (RTCP) for web applications exploiting user session data and hamming code distance. The proposed technique utilises user session data to reorder test cases such that test cases which cover the ‘most frequently accessed subset of pages together’ are given higher priority. The coverage information of user session data along with its frequency appearance and test cases are converted to hamming code. These hamming codes are used to calculate the coverage similarity between user access pattern and the test cases. Further, the hamming code distance is incorporated with frequency of appearance to calculate a weighted average distance among user session data and test cases. Finally, the test cases with a lesser weighted average distance are given higher priority.