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
Link To Document :
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