Exploiting user session data is a promising approach for testing a Web application. However, the effectiveness of user session testing techniques depends on the set of collected user session data: the wider this set, the greater the capability of the approach to detect failures, but the wider the user session data set, the greater the cost of collecting, analysing and storing data.

In this paper, a technique for reducing a set of user sessions into an equivalent smaller one will be proposed. This technique allows equivalent user behaviours included in user sessions to be identified and classified, and produces a reduced set of user sessions that can be used to design test suites with a reduced effort. Some preliminary case studies were carried out to validate the proposed technique and to evaluate its effectiveness. Results of a case study will be presented in the paper.