Most of today's software users interact with the software through a graphical user interfac (GUI), which is a representative of the broader class of event-driven software (EDS). As the correctness of the GUI is necessary to ensure the correctness of the overall software, its quality assurance (QA) is becoming increasingly important. During software testing, an important QA technique, test cases are created and executed on the software. For GUIs, test cases are modeled as sequences of user input events. Because each possible sequence of user events may potentially be a test case and because today's GUIs offer enormous flexibility to end users, in principle, GUI testing requires a prohibitively large number of test cases. Any practical test case generation technique must sample the vast GUI input space. Existing techniques are either extremely resource intensive or do not adequately model complex GUI behaviors, thereby limiting fault detection.

This research develops new models, algorithms, and metrics for automated GUI test case generation. A novel aspect of this work is its use of software runtime information collected as feedback during GUI test case execution, and used to generate additional test cases that model complex GUI behaviors. One set of empirical studies show that the feedback directed technique significantly improves upon existing techniques and helps to identify serious problems in fielded GUIs. Another set of studies conducted on in-house software applications show that the test suites generated by the new technique outperform their coverage equivalent counterparts in terms of fault detection.

Although the focus of this work is on the GUI domain, the techniques developed are general and are applicable to the broader class of EDS. In fact, this work has already had an impact on research and practice of testing other EDS. In particular, the work has been extended by other researchers to test web applications.