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GUI Test Coverage Analysis using NSGA II
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Abdul Rauf1,Eisa A. Aleisa2,Imam Bakhsh3
*1 College of Computer & Information Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, KSA, Saudi Arabia,
Email : rauf.amlik@ccis.imamu.edu.sa
2 College of Computer & Information Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, KSA, Saudi Arabia,
Email : aleisa@ccis.imamu.edu.sa
3 College of Computer & Information Science, Imam Mohammad Ibn Saud Islamic University, Riyadh, KSA, Saudi Arabia,
Email : ibakhsh@ccis.imamu.edu.sa
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Abstract
.Graphical User Interface (GUI) is a mean of interaction between an end user and a software system. Software systems have gained an unprecedented popularity in last twenty years or so and the biggest factor behind this success is Graphical user interface. Software developing companies and teams have always shown a thirst for fully assured high quality software. To fulfill this deep desire of companies, software must go through an intensive testing, but it seems almost impossible to test a GUI application manually due to complexity involve in such effort. Obvious alternative is to go for automated testing. Models or Graphs are being considered as basis for automated GUI testing. Event-flow graph is one of several efforts towards automation of GUI testing. Thorough testing to satisfy the test organization or team’s demands is also a terminology, facing lack of consensus among different researchers. Usually test criterion corresponds a “coverage function” that measures how much of the automatically generated optimization parameters satisfies the given test criterion. Our past work has demonstrated that with the help of evolutionary algorithms and event flow representation we can get promising test coverage of GUI applications. Now we are going to extend our previous work and proposing the use of an evolutionary algorithm to gain multiple objectives. These objectives are to gain maximum coverage while keeping number of test cases at minimum side, and the evolutionary algorithm we are going to use for this purpose is Non-dominated Sorting Genetic Algorithm II ( NSGA-II).
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Keywords
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NSGA; Testing Event Driven Software; Search Based Software Testing; GUI Testing
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URL: http://dx.doi.org/10.7321/jscse.v3.n3.48
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