Random Test Generation from Regular Expressions for Graphical User Interface (GUI) Testing

Abstract

Generation of test sequences, that is, (user) inputs - expected (system) outputs, is an important task of testing of graphical user interfaces (GUI). This work proposes an approach to randomly generate test sequences that might he used for comparison with existing GUI testing techniques to evaluate their efficiency. The proposed approach first models CUI under test by a finite state machine (FSM) and then converts it to a regular expression (RE). A tool based on a special technique we developed analyzes the RE to fulfill missing context information such as the position of a symbol in the RE. The result is a context table representing the RE. The proposed approach traverses the context table to generate the test sequences. To do this, the approach repeatedly selects a symbol in the table, starting from the initial symbol, in a random manner until reaching a special, finalizing symbol for constructing a test sequence. Thus, the approach uses a symbol coverage criterion to assess the adequacy of the test generation. To evaluate the approach, mutation testing is used. The proposed technique is to a great extent implemented and is available as a tool called PQ-Ran Test (PQ-analysis based Random Test Generation). A case study demonstrates the proposed approach and analyzes its effectiveness by mutation testing.