PMothra: scheduling mutants for execution on a hypercube
TAV3 Proceedings of the ACM SIGSOFT '89 third symposium on Software testing, analysis, and verification
A Fortran language system for mutation-based software testing
Software—Practice & Experience
Investigations of the software testing coupling effect
ACM Transactions on Software Engineering and Methodology (TOSEM)
PIE: A Dynamic Failure-Based Technique
IEEE Transactions on Software Engineering
Mutation analysis using mutant schemata
ISSTA '93 Proceedings of the 1993 ACM SIGSOFT international symposium on Software testing and analysis
An experimental determination of sufficient mutant operators
ACM Transactions on Software Engineering and Methodology (TOSEM)
Testing object-oriented systems: models, patterns, and tools
Testing object-oriented systems: models, patterns, and tools
Mutation analysis of program test data
Mutation analysis of program test data
Is mutation an appropriate tool for testing experiments?
Proceedings of the 27th international conference on Software engineering
MuJava: a mutation system for java
Proceedings of the 28th international conference on Software engineering
Software Testing Research: Achievements, Challenges, Dreams
FOSE '07 2007 Future of Software Engineering
Weak Mutation Testing and Completeness of Test Sets
IEEE Transactions on Software Engineering
Sufficient mutation operators for measuring test effectiveness
Proceedings of the 30th international conference on Software engineering
Information and Software Technology
(Un-)Covering Equivalent Mutants
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
MAJOR: An efficient and extensible tool for mutation analysis in a Java compiler
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
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Assessing testing strategies and test sets is a crucial part of software testing. Mutation analysis is, among other approaches, a suitable technique for this purpose. However, compared with other methods it is rather time-consuming and applying mutation analysis to large software systems is still problematic. This paper presents a versatile approach, called conditional mutation, which increases the efficiency of mutation analysis. This new method significantly reduces the time overhead for generating and executing the mutants. Results are reported for eight investigated programs up to 373,000 lines of code and 406,000 generated mutants. Furthermore, conditional mutation has been integrated into the Java 6 Standard Edition compiler. Thus, it is widely applicable and not limited to a certain testing tool or framework.