An experimental evaluation of data flow and mutation testing
Software—Practice & Experience
All-uses vs mutation testing: an experimental comparison of effectiveness
Journal of Systems and Software
Software unit test coverage and adequacy
ACM Computing Surveys (CSUR)
Test Driven Development: By Example
Test Driven Development: By Example
ISSRE '02 Proceedings of the 13th International Symposium on Software Reliability Engineering
On the Effectiveness of Mutation Analysis as a Black Box Testing Technique
ASWEC '01 Proceedings of the 13th Australian Conference on Software Engineering
An experimental mutation system for Java
ACM SIGSOFT Software Engineering Notes
Is mutation an appropriate tool for testing experiments?
Proceedings of the 27th international conference on Software engineering
Evaluation of mutation testing for object-oriented programs
Proceedings of the 28th international conference on Software engineering
The class-level mutants of MuJava
Proceedings of the 2006 international workshop on Automation of software test
TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
Jumble Java Byte Code to Measure the Effectiveness of Unit Tests
TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
An Empirical Evaluation of the MuJava Mutation Operators
TAICPART-MUTATION '07 Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION
On guiding the augmentation of an automated test suite via mutation analysis
Empirical Software Engineering
Mutation operators for JADE mobile agent systems
Proceedings of the 3rd International Conference on Information and Communication Systems
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Mutation testing has historically been used to assess the fault-finding effectiveness of a test suite or other verification technique. Mutation analysis, rather, entails augmenting a test suite to detect all killable mutants. Concerns about the time efficiency of mutation analysis may prohibit its widespread, practical use. The goal of our research is to assess the effectiveness of the mutation analysis process when used by software testers to augment a test suite to obtain higher statement coverage scores. We conducted two empirical studies and have shown that mutation analysis can be used by software testers to effectively produce new test cases and to improve statement coverage scores in a feasible amount of time. Additionally, we find that our user study participants view mutation analysis as an effective but relatively expensive technique for writing new test cases. Finally, we have shown that the choice of mutation tool and operator set can play an important role in determining how efficient mutation analysis is for producing new test cases.