A theory of diagnosis from first principles
Artificial Intelligence
An experimental determination of sufficient mutant operators
ACM Transactions on Software Engineering and Methodology (TOSEM)
Simplifying and Isolating Failure-Inducing Input
IEEE Transactions on Software Engineering
Experimental Evaluation of Program Slicing for Fault Localization
Empirical Software Engineering
MuJava: an automated class mutation system: Research Articles
Software Testing, Verification & Reliability
Experimental evaluation of using dynamic slices for fault location
Proceedings of the sixth international symposium on Automated analysis-driven debugging
Empirical evaluation of the tarantula automatic fault-localization technique
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Automated Source-Level Error Localization in Hardware Designs
IEEE Design & Test
On the Accuracy of Spectrum-based Fault Localization
TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
Automatically finding patches using genetic programming
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
MINION: A Fast, Scalable, Constraint Solver
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Spectrum-Based Multiple Fault Localization
ASE '09 Proceedings of the 2009 IEEE/ACM International Conference on Automated Software Engineering
Generating Distinguishing Tests Using the Minion Constraint Solver
ICSTW '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification, and Validation Workshops
Using Mutation to Automatically Suggest Fixes for Faulty Programs
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
Diagnosing errors in dbc programs using constraint programming
CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
An empirical study on the use of mutant traces for diagnosis of faults in deployed systems
Journal of Systems and Software
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Tools for automated fault localization usually generate too many bug candidates depending on the underlying technique. Hence, further information is required in order to further restrict the bug candidates. Approaches that rely on specific knowledge of the program to be debugged like variable values at specific position in the source code, are not easily accessible for users especially in case of software maintenance. In order to avoid this problem we suggest to integrate testing for restricting the number of bug candidates. In particular, we suggest to compute possible corrections of the program and from this, distinguishing test cases. A distinguishing test case is a test that reveals different output values for two given program variants, given the same input values. Besides the formal definitions and algorithms, we present the first empirical results of our approach. The use of mutations and distinguishing test cases substantially reduces the number of bug candidates.