• DocumentCode
    259643
  • Title

    Feature Selections for Effectively Localizing Faulty Events in GUI Applications

  • Author

    Xiaozhen Xue ; Yulei Pang ; Namin, Akbar Siami

  • Author_Institution
    Dept. of Comput. Sci., Texas Tech Univ., Lubbock, TX, USA
  • fYear
    2014
  • fDate
    3-6 Dec. 2014
  • Firstpage
    306
  • Lastpage
    311
  • Abstract
    Due to the complex causality of failure and the special characteristics of test cases, the faults in GUI (Graphic User Interface) applications are difficult to localize. This paper adapts feature selection algorithms to localize GUI-related faults in a given program. Features are defined as the subsequences of events executed. By employing statistical feature ranking techniques, the events can be ranked by the suspiciousness of events being responsible to exhibit faulty behavior. The features defined in a given source code implementing (event handle) the underlying event are then ranked in suspiciousness order. The evaluation of the proposed technique based on some open source Java projects verified the effectiveness of this feature selection based fault localization technique for GUI applications.
  • Keywords
    Java; causality; feature selection; graphical user interfaces; project management; public domain software; source code (software); statistical analysis; GUI application; complex failure causality; faulty event localization; feature selection algorithms; feature selection based fault localization technique; graphic user interface applications; open source Java projects; source code; statistical feature ranking techniques; Feature extraction; Graphical user interfaces; Java; Software; Software algorithms; Testing; Vectors; GUI; faults localization; feature selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2014 13th International Conference on
  • Conference_Location
    Detroit, MI
  • Type

    conf

  • DOI
    10.1109/ICMLA.2014.55
  • Filename
    7033132