Proteum/FL: A tool for localizing faults using mutation analysis

Fault diagnosis is the process of analyzing programs with the aim of identifying the code fragments that are faulty. It has been identified as one of the most expensive and time consuming tasks of software development. Even worst, this activity is usually accomplished based on manual analysis. To this end, automatic or semi-automatic fault diagnosis approaches are useful in assisting software developers. Hence, they can play an essential role in decreasing the overall development cost. This paper presents Proteum/FL, a mutation analysis tool for diagnosing previously detected faults. Given an ANSI-C program and a set of test cases, Proteum/FL returns a list of program statements ranked according to their likelihood of being faulty. The tool differs from the rest of the mutation analysis and fault diagnosis tools by employing mutation analysis as a means of diagnosing program faults. It therefore demonstrates the effective use of mutation in supporting both testing and debugging activities.

[1]  Mark Harman,et al.  An Analysis and Survey of the Development of Mutation Testing , 2011, IEEE Transactions on Software Engineering.

[2]  Lee Naish,et al.  A model for spectra-based software diagnosis , 2011, TSEM.

[3]  Wynne Hsu,et al.  DESIGN OF MUTANT OPERATORS FOR THE C PROGRAMMING LANGUAGE , 2006 .

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

[5]  Mike Papadakis,et al.  Evaluating Mutation Testing Alternatives: A Collateral Experiment , 2010, 2010 Asia Pacific Software Engineering Conference.

[6]  Yue Jia,et al.  MILU: A Customizable, Runtime-Optimized Higher Order Mutation Testing Tool for the Full C Language , 2008, Testing: Academic & Industrial Conference - Practice and Research Techniques (taic part 2008).

[7]  W. Eric Wong Mutation Testing for the New Century , 2001 .

[8]  Morgan B Kaufmann,et al.  Mutation Testing for the New Century , 2002, Computer.

[9]  Raúl A. Santelices,et al.  Lightweight fault-localization using multiple coverage types , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[10]  A. Jefferson Offutt,et al.  MuJava: an automated class mutation system , 2005, Softw. Test. Verification Reliab..

[11]  Wes Masri,et al.  Cleansing Test Suites from Coincidental Correctness to Enhance Fault-Localization , 2010, 2010 Third International Conference on Software Testing, Verification and Validation.

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

[13]  Mike Papadakis,et al.  Automatic Mutation Test Case Generation via Dynamic Symbolic Execution , 2010, 2010 IEEE 21st International Symposium on Software Reliability Engineering.

[14]  Mike Papadakis,et al.  Automatically performing weak mutation with the aid of symbolic execution, concolic testing and search-based testing , 2011, Software Quality Journal.

[15]  Yong Rae Kwon,et al.  MuJava: an automated class mutation system: Research Articles , 2005 .

[16]  Yves Le Traon,et al.  Using Mutants to Locate "Unknown" Faults , 2012, 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation.

[17]  Rui Abreu,et al.  Zoltar: a spectrum-based fault localization tool , 2009, SINTER '09.

[18]  Mike Papadakis,et al.  Mutation based test case generation via a path selection strategy , 2012, Inf. Softw. Technol..

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

[20]  Aditya P. Mathur,et al.  Interface Mutation: An Approach for Integration Testing , 2001, IEEE Trans. Software Eng..

[21]  A.J.C. van Gemund,et al.  On the Accuracy of Spectrum-based Fault Localization , 2007, Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007).

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

[23]  James H. Andrews,et al.  Evaluating the Accuracy of Fault Localization Techniques , 2009, 2009 IEEE/ACM International Conference on Automated Software Engineering.