PSO based Automated Test Coverage Analysis of Event Driven Systems

Abstract

Graphical User Interface (GUI, pronounced sometimes as gooey as well) was first developed in 1981 and has become an essence for today's computing. A GUI contains graphical objects having certain distinct values which can be used to determine the state of the GUI at any time. Developing organizations always desire to thoroughly test the software to get maximum confidence about its quality, but this requires gigantic effort to test a GUI application due to complexity involve in such applications. This problem has led to automate GUI testing and different techniques have been proposed for automated GUI Testing. Event-flow graph is a fresh breach in the field of automated GUI testing. As control-flow graph, another GUI model represents all possible execution paths in a program; in the same way, event-flow model represents all promising progressions of events that can be executed on the GUI. Another challenging question in software testing is, how much testing is enough? There are few measures that can be used to provide guidance on the quality of an automatic test suite as development proceeds. Particle swarm optimization (PSO) algorithm searches for best possible test parameter combinations that are according to some predefined test criterion. Usually this test criterion corresponds a “coverage function” that measures how much of the automatically generated optimization parameters satisfies the given test criterion. In this paper, we have tried to exploit event driven nature of GUI. Based on this nature, we have presented a GUI testing and coverage analysis technique based on PSO.

Keywords::

• GUI testing
• Particle swarm optimization
• Coverage criterion
• Coverage analysis
• Event flow
• Test data generation
• Test path
• Automation testing

Additional information

Notes on contributors

Abdul Rauf

Abdul Rauf is currently working as assistant professor at College of Computer and Information Sciences, Al-Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. He completed his Ph.D. in Computer Sciences from National University of Computer & Emerging Sciences (NUCES) Islamabad, Pakistan. His research interests include search based software engineering, software process and project management and software quality assurance. He can be reached at [email protected].

Eisa A. Aleisa

Eisa Abdullah Aleisa received Ph.D. degree from the Department of Computer Science Lehigh University, Bethlehem, PA, USA in 2000. He is currently working as the Dean of College of Computer and Information Sciences at Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. His research interests include heterogeneous distributed networks, image processing and machine learning techniques. Email: [email protected]