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Advances in Software Engineering
Volume 2012 (2012), Article ID 642983, 12 pages
Research Article

Program Spectra Analysis with Theory of Evidence

Department of Computer Science, Texas Tech University, Lubbock, TX 79409-3104, USA

Received 30 August 2011; Revised 4 January 2012; Accepted 8 January 2012

Academic Editor: Chin-Yu Huang

Copyright © 2012 Rattikorn Hewett. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents an approach to automatically analyzing program spectra, an execution profile of program testing results for fault localization. Using a mathematical theory of evidence for uncertainty reasoning, the proposed approach estimates the likelihood of faulty locations based on evidence from program spectra. Our approach is theoretically grounded and can be computed online. Therefore, we can predict fault locations immediately after each test execution is completed. We evaluate the approach by comparing its performance with the top three performing fault localizers using a benchmark set of real-world programs. The results show that our approach is at least as effective as others with an average effectiveness (the reduction of the amount of code examined to locate a fault) of 85.6% over 119 versions of the programs. We also study the quantity and quality impacts of program spectra on our approach where the quality refers to the spectra support in identifying that a certain unit is faulty. The results show that the effectiveness of our approach slightly improves with a larger number of failed runs but not with a larger number of passed runs. Program spectra with support quality increases from 1% to 100% improves the approach's effectiveness by 3.29%.