An experimental determination of sufficient mutant operators
ACM Transactions on Software Engineering and Methodology (TOSEM)
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)
The case for collaborative programming
Communications of the ACM
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
All I really need to know about pair programming I learned in kindergarten
Communications of the ACM
Pair Programming Illuminated
Mutation 2000: uniting the orthogonal
Mutation testing for the new century
Test Driven Development: By Example
Test Driven Development: By Example
Empirical Software Engineering
Hints for Reviewing Empirical Work in Software Engineering
Empirical Software Engineering
Strengthening the Case for Pair Programming
IEEE Software
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
A measure of test case completeness (software, engineering)
A measure of test case completeness (software, engineering)
Are Reviews an Alternative to Pair Programming?
Empirical Software Engineering
An experimental mutation system for Java
ACM SIGSOFT Software Engineering Notes
A multiple case study on the impact of pair programming on product quality
Proceedings of the 27th international conference on Software engineering
Extreme Programming Explained: Embrace Change (2nd Edition)
Extreme Programming Explained: Embrace Change (2nd Edition)
The effect of code coverage on fault detection under different testing profiles
A-MOST '05 Proceedings of the 1st international workshop on Advances in model-based testing
Analysis of the interaction between practices for introducing XP effectively
Proceedings of the 28th international conference on Software engineering
MuJava: a mutation system for java
Proceedings of the 28th international conference on Software engineering
Evaluation of mutation testing for object-oriented programs
Proceedings of the 28th international conference on Software engineering
Evaluating Pair Programming with Respect to System Complexity and Programmer Expertise
IEEE Transactions on Software Engineering
Testing Programs with the Aid of a Compiler
IEEE Transactions on Software Engineering
Introduction to Software Testing
Introduction to Software Testing
Proceedings of the 2005 conference on Software Engineering: Evolution and Emerging Technologies
PROFES'06 Proceedings of the 7th international conference on Product-Focused Software Process Improvement
Pair programming vs. side-by-side programming
EuroSPI'05 Proceedings of the 12th European conference on Software Process Improvement
Is external code quality correlated with programming experience or feelgood factor?
XP'06 Proceedings of the 7th international conference on Extreme Programming and Agile Processes in Software Engineering
Capable Leader and Skilled and Motivated Team Practices to Introduce eXtreme Programming
Balancing Agility and Formalism in Software Engineering
Information and Software Technology
Object-Oriented testing capabilities and performance evaluation of the c# mutation system
CEE-SET'09 Proceedings of the 4th IFIP TC 2 Central and East European conference on Advances in Software Engineering Techniques
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Code coverage and mutation score measure how thoroughly tests exercise programs and how effective they are, respectively. The objective is to provide empirical evidence on the impact of pair programming on both, thoroughness and effectiveness of test suites, as pair programming is considered one of the practices that can make testing more rigorous, thorough and effective. A large experiment with MSc students working solo and in pairs was conducted. The subjects were asked to write unit tests using JUnit, and to follow test-driven development approach, as suggested by eXtreme Programming methodology. It appeared that branch coverage, as well as mutation score indicator (the lower bound on mutation score), was not significantly affected by using pair programming, instead of solo programming. However, slight but insignificant positive impact of pair programming on mutations score indicator was noticeable. The results do not support the positive impact of pair programming on testing to make it more effective and thorough. The generalization of the results is limited due to the fact that MSc students participated in the study. It is possible that the benefits of pair programming will exceed the results obtained in this experiment for larger, more complex and longer projects.