Fuzzy Adaptive Teaching Learning-based Optimization Strategy for GUI Functional Test Cases Generation
摘要：Graphical User Interface（GUI） visualizes computer programs for the purpose of facilitating interaction between users and various computing devices. Today’s computers, smart phones and even small devices such as watches are equipped with GUIs. Unlike command based interaction, GUI uses images, labels, push buttons, radio buttons, etc. for the effective communication of users with a software system. GUI testing is a critical part of software testing as it is the door to the actual functionality of software. For the quality assurance, GUI functional testing of a software validates proper interaction between the interface and the user without considering any coding details. In this paper, a strategy based on fuzzy Adaptive Teaching Learning-based Optimization（ATLBO） algorithm, a variant of the basic Teaching Learning-based Optimization（TLBO） algorithm, for GUI functional testing is proposed. ATLBO utilizes Event-Interaction Graph（EIG） for the generation of quality test cases. The proposed strategy has produced competitive experimental results against the basic TLBO and other test case generation algorithms.