Mike Papadakis, Nicos Malevris, Marinos Kintis


Mutation Testing is considered to be one of the most powerful techniques for unit testing and at the same time one of the most expensive. The principal expense of mutation is the vast number of imposed test requirements, many of which cannot be satisfied. In order to overcome these limitations, researchers have proposed many cost reduction techniques, such as selective mutation, weak mutation and a novel approach based on mutant combination, which combines first order mutants to generate second order ones. An experimental comparison involving weak mutation, strong mutation and various proposed strategies was conducted. The experiment shows that all proposed approaches are quite effective in general as they result in high collateral coverage of strong mutation (approximately 95%), while recording remarkable effort savings. Additionally, the results suggest that some of the proposed approaches are more effective than others making it possible to reduce the mutation testing application cost with only a limited impact on its effectiveness.


  1. Agrawal, H. 1994. Dominators, super blocks, and program coverage. Proceedings of the 21st ACM SIGPLANSIGACT symposium on Principles of programming languages. Portland, Oregon, United States: ACM.
  2. Andrews, J. H., Briand, L. C., Labiche, Y. & Namin, A. S. 2006. Using Mutation Analysis for Assessing and Comparing Testing Coverage Criteria. IEEE Trans. Softw. Eng., 32, 608-624.
  3. Demillo, R. A., Lipton, R. J. & Sayward, F. G. 1978. Hints on Test Data Selection: Help for the Practicing Programmer. Computer, 11, 34-41.
  4. Hamlet, R. G. 1977. Testing Programs with the Aid of a Compiler. IEEE Trans. Softw. Eng., 3, 279-290.
  5. Howden, W. E. 1982. Weak Mutation Testing and Completeness of Test Sets. IEEE Trans. Softw. Eng., 8, 371-379.
  6. Kintis, M. 2010. Mutation testing and its approximations. Master Thesis (in Greek), Athens University of Economics and Business.
  7. MA, Y.-S., Offutt, J. & Kwon, Y. R. 2005. MuJava: an automated class mutation system: Research Articles. Softw. Test. Verif. Reliab., 15, 97-133.
  8. Malevris, N. & Yates, D. F. 2006. The collateral coverage of data flow criteria when branch testing. Information and Software Technology, 48, 676-686.
  9. Offutt, A. J. & Lee, S. D. 1994. An Empirical Evaluation of Weak Mutation. IEEE Trans. Softw. Eng., 20, 337- 344.
  10. Offutt, A. J. & Untch, R. H. 2001. Mutation 2000: uniting the orthogonal. Mutation testing for the new century. Kluwer Academic Publishers.
  11. Papadakis, M. & Malevris, N. 2010. An Empirical Evaluation of the First and Second Order Mutation Testing Strategies. Proceedings of the 5th International Workshop on Mutation Analysis (MUTATION'10). Paris, France.
  12. Papadakis, M., Malevris, N. & Kallia, M. 2010. Towards Automating the Generation of Mutation Tests. AST 2010. Cape Town.
  13. Polo, M., Piattini, M. & GarcĂ­a-RodrĂ­guez, I. 2009. Decreasing the cost of mutation testing with secondorder mutants. Software Testing, Verification and Reliability, 19, 111-131.

Paper Citation

in Harvard Style

Papadakis M., Malevris N. and Kintis M. (2010). MUTATION TESTING STRATEGIES - A Collateral Approach . In Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-8425-23-2, pages 325-328. DOI: 10.5220/0003012903250328

in Bibtex Style

author={Mike Papadakis and Nicos Malevris and Marinos Kintis},
title={MUTATION TESTING STRATEGIES - A Collateral Approach},
booktitle={Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,},

in EndNote Style

JO - Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,
SN - 978-989-8425-23-2
AU - Papadakis M.
AU - Malevris N.
AU - Kintis M.
PY - 2010
SP - 325
EP - 328
DO - 10.5220/0003012903250328