On the utility of dominator mutants for mutation testing

Mutation testing has been shown to support the generation of test sets that are highly effective at detecting faults. However, practitioner adoption of mutation testing has been minimal in part because of problems that arise from the huge numbers of redundant and equivalent mutants that are generated. The research described here examines the relationship between mutants and attempts to reduce the number of redundant and equivalent mutants in order to make mutation testing more practical for the software tester.

[1]  Akbar Siami Namin,et al.  Sufficient mutation operators for measuring test effectiveness , 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.

[2]  A. Jefferson Offutt,et al.  Empirical Evaluation of the Statement Deletion Mutation Operator , 2013, 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation.

[3]  Sarfraz Khurshid,et al.  Operator-based and random mutant selection: Better together , 2013, 2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE).

[4]  J. A. Acree.  On mutation , 1980 .

[5]  A. Jefferson Offutt,et al.  Experimental Evaluation of SDL and One-Op Mutation for C , 2014, 2014 IEEE Seventh International Conference on Software Testing, Verification and Validation.

[6]  Yves Le Traon,et al.  Threats to the validity of mutation-based test assessment , 2016, ISSTA.

[7]  A. Jefferson Offutt,et al.  Growing a Reduced Set of Mutation Operators , 2014, 2014 Brazilian Symposium on Software Engineering.

[8]  A. Jefferson Offutt,et al.  Static analysis of mutant subsumption , 2015, 2015 IEEE Eighth International Conference on Software Testing, Verification and Validation Workshops (ICSTW).

[9]  Auri Marcelo Rizzo Vincenzi,et al.  Toward the determination of sufficient mutant operators for C † , 2001, Softw. Test. Verification Reliab..

[10]  Sarfraz Khurshid,et al.  Directed incremental symbolic execution , 2011, PLDI '11.

[11]  Richard J. Lipton,et al.  Hints on Test Data Selection: Help for the Practicing Programmer , 1978, Computer.

[12]  W. Eric Wong,et al.  Reducing the cost of mutation testing: An empirical study , 1995, J. Syst. Softw..

[13]  Timothy Alan Budd,et al.  Mutation analysis of program test data , 1980 .

[14]  Roland H. Untch.  On reduced neighborhood mutation analysis using a single mutagenic operator , 2009, ACM-SE 47.

[15]  A. Jefferson Offutt,et al.  Are We There Yet? How Redundant and Equivalent Mutants Affect Determination of Test Completeness , 2016, 2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW).

[16]  Gregg Rothermel,et al.  An experimental determination of sufficient mutant operators , 1996, TSEM.

[17]  Mark Harman,et al.  A study of equivalent and stubborn mutation operators using human analysis of equivalence , 2014, ICSE.

[18]  A. Jefferson Offutt,et al.  Analyzing the validity of selective mutation with dominator mutants , 2016, SIGSOFT FSE.

[19]  Tao Xie,et al.  Is operator-based mutant selection superior to random mutant selection? , 2010, 2010 ACM/IEEE 32nd International Conference on Software Engineering.

[20]  Alex Groce,et al.  Do Mutation Reduction Strategies Matter , 2015 .

[21]  Mark Harman,et al.  Constructing Subtle Faults Using Higher Order Mutation Testing , 2008, 2008 Eighth IEEE International Working Conference on Source Code Analysis and Manipulation.

[22]  A.P. Mathur.  Performance, effectiveness, and reliability issues in software testing , 1991, [1991] Proceedings The Fifteenth Annual International Computer Software & Applications Conference.

[23]  A. Jefferson Offutt,et al.  Mutant Subsumption Graphs , 2014, 2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops.

[24]  Pankaj Sharma,et al.  MuRanker: a mutant ranking tool , 2015, Softw. Test. Verification Reliab..

[25]  A. Jefferson Offutt,et al.  Establishing Theoretical Minimal Sets of Mutants , 2014, 2014 IEEE Seventh International Conference on Software Testing, Verification and Validation.