A Grouping-Based Strategy to Improve the Effectiveness of Fault Localization Techniques

Fault localization is one of the most expensive activities of program debugging, which is why the recent years have witnessed the development of many different fault localization techniques. This paper proposes a grouping-based strategy that can be applied to various techniques in order to boost their fault localization effectiveness. The applicability of the strategy is assessed over – Tarantula and a radial basis function neural network-based technique; across three different sets of programs (the Siemens suite, grep and gzip). Results are suggestive that the grouping-based strategy is capable of significantly improving the fault localization effectiveness and is not limited to any particular fault localization technique. The proposed strategy does not require any additional information than what was already collected as input to the fault localization technique, and does not require the technique to be modified in any way.

[1]  Iris Vessey,et al.  Expertise in Debugging Computer Programs , 1984 .

[2]  H. Cleve,et al.  Locating causes of program failures , 2005, Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005..

[3]  Lei Zhao,et al.  A Crosstab-based Statistical Method for Effective Fault Localization , 2008, 2008 1st International Conference on Software Testing, Verification, and Validation.

[4]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[5]  Joseph Robert Horgan,et al.  Fault localization using execution slices and dataflow tests , 1995, Proceedings of Sixth International Symposium on Software Reliability Engineering. ISSRE'95.

[6]  Yu Qi,et al.  Bp Neural Network-Based Effective Fault Localization , 2009, Int. J. Softw. Eng. Knowl. Eng..

[7]  Robert M. Hierons.  Avoiding coincidental correctness in boundary value analysis , 2006, TSEM.

[8]  Yves Le Traon,et al.  Improving test suites for efficient fault localization , 2006, ICSE.

[9]  Chao Liu,et al.  Statistical Debugging: A Hypothesis Testing-Based Approach , 2006, IEEE Transactions on Software Engineering.

[10]  Steven P. Reiss,et al.  Fault localization with nearest neighbor queries , 2003, 18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings..

[11]  Yan Shi,et al.  Using an RBF Neural Network to Locate Program Bugs , 2008, 2008 19th International Symposium on Software Reliability Engineering (ISSRE).

[12]  A. Zeller.  Isolating cause-effect chains from computer programs , 2002, SIGSOFT '02/FSE-10.

[13]  Xiangyu Zhang,et al.  Locating faults through automated predicate switching , 2006, ICSE.

[14]  Mary Jean Harrold,et al.  Empirical evaluation of the tarantula automatic fault-localization technique , 2005, ASE.

[15]  Gregg Rothermel,et al.  On the Use of Mutation Faults in Empirical Assessments of Test Case Prioritization Techniques , 2006, IEEE Transactions on Software Engineering.

[16]  Mary Jean Harrold,et al.  Debugging in Parallel , 2007, ISSTA '07.

[17]  Shing-Chi Cheung,et al.  Taming coincidental correctness: Coverage refinement with context patterns to improve fault localization , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[18]  Lionel C. Briand,et al.  Is mutation an appropriate tool for testing experiments? , 2005, ICSE.

[19]  Iris Vessey,et al.  Expertise in Debugging Computer Programs: A Process Analysis , 1984, Int. J. Man Mach. Stud..

[20]  Michael I. Jordan,et al.  Bug isolation via remote program sampling , 2003, PLDI.

[21]  Lionel C. Briand,et al.  Using Mutation Analysis for Assessing and Comparing Testing Coverage Criteria , 2006, IEEE Transactions on Software Engineering.

[22]  Mary Jean Harrold,et al.  An empirical study of the effects of test-suite reduction on fault localization , 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.

[23]  Yu Qi,et al.  Effective program debugging based on execution slices and inter-block data dependency , 2006, J. Syst. Softw..

[24]  Peter Zoeteweij,et al.  An Evaluation of Similarity Coefficients for Software Fault Localization , 2006, 2006 12th Pacific Rim International Symposium on Dependable Computing (PRDC'06).

[25]  Byoungju Choi,et al.  A family of code coverage-based heuristics for effective fault localization , 2010, J. Syst. Softw..

[26]  W. K. Chan,et al.  Coincidental Correctness: Refine Code Coverage with Context Pattern to Improve Fault Localization , 2009, ICSE 2009.