Regression test selection techniques: A survey, Informatica, vol.35, issue.3, pp.289-321, 2011. ,
Simplifying decision trees: A survey, The Knowledge Engineering Review, vol.12, issue.01, pp.1-40, 1997. ,
DOI : 10.1017/S0269888997000015
Using Machine Learning to Refine Black-Box Test Specifications and Test Suites, 2008 The Eighth International Conference on Quality Software, pp.135-144, 2008. ,
DOI : 10.1109/QSIC.2008.5
URL : http://squall.sce.carleton.ca/pubs/tech_report/TR_SCE-07-05.pdf
Dividing strategies for the optimization of a test suite, Information Processing Letters, vol.60, issue.3, pp.135-141, 1996. ,
DOI : 10.1016/S0020-0190(96)00135-4
Decision tree reduction, Journal of the ACM, vol.37, issue.4, pp.815-842, 1990. ,
DOI : 10.1145/96559.96576
Discrete decision theory: manipulations, Theoretical Computer Science, vol.54, issue.2-3, pp.215-236, 1987. ,
DOI : 10.1016/0304-3975(87)90130-7
URL : https://doi.org/10.1016/0304-3975(87)90130-7
Progress in Pattern Recognition 2, chap. Decision Trees in Pattern Recognition, pp.189-240, 1985. ,
Z3: An Efficient SMT Solver, 14th Int. Conference on Tools and Algorithms for the Construction and Analysis of Systems, pp.337-340, 2008. ,
DOI : 10.1007/978-3-540-78800-3_24
Hints on Test Data Selection: Help for the Practicing Programmer, Computer, vol.11, issue.4, pp.34-41, 1978. ,
DOI : 10.1109/C-M.1978.218136
Test-Suite Reduction Does Not Necessarily Require Executing the Program under Test, 2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), pp.23-30, 2016. ,
DOI : 10.1109/QRS-C.2016.8
Empirical study of correlation between mutation score and model inference based test suite adequacy assessment, Proceedings of the 11th International Workshop on Automation of Software Test, AST '16, pp.43-49, 2016. ,
DOI : 10.1109/RAISE.2015.11
Redundancy Based Test-Suite Reduction, Int. Conf. on Fund. Approaches to Software Eng, pp.291-305, 2007. ,
DOI : 10.1007/978-3-540-71289-3_23
URL : http://www.ist.tugraz.at/staff/fraser/papers//fase07.pdf
FLOWER: optimal test suite reduction as a network maximum flow, Proceedings of the 2014 International Symposium on Software Testing and Analysis, ISSTA 2014, pp.171-180, 2014. ,
DOI : 10.1145/2610384.2610416
The WEKA data mining software, ACM SIGKDD Explorations Newsletter, vol.11, issue.1, pp.10-18, 2009. ,
DOI : 10.1145/1656274.1656278
A methodology for controlling the size of a test suite, ACM Transactions on Software Engineering and Methodology, vol.2, issue.3, pp.270-285, 1993. ,
DOI : 10.1145/152388.152391
The Elements of Statistical Learning, 2009. ,
Constructing optimal binary decision trees is NP-complete, Information Processing Letters, vol.5, issue.1, pp.15-17, 1976. ,
DOI : 10.1016/0020-0190(76)90095-8
The major mutation framework: efficient and scalable mutation analysis for Java, Proceedings of the 2014 International Symposium on Software Testing and Analysis, ISSTA 2014, pp.433-436, 2014. ,
DOI : 10.1145/2610384.2628053
Reducibility among Combinatorial Problems, pp.85-103, 1972. ,
DOI : 10.1007/978-3-540-68279-0_8
Decision Trees and Diagrams, ACM Computing Surveys, vol.14, issue.4, pp.593-623, 1982. ,
DOI : 10.1145/356893.356898
Procedures for reducing the size of coveragebased test sets, Proceedings of the 12th International Conference on Testing Computer Software. pp, pp.111-123, 1995. ,
The category-partition method for specifying and generating fuctional tests, Communications of the ACM, vol.31, issue.6, pp.676-686, 1988. ,
DOI : 10.1145/62959.62964
Reduction of test suites using mutation, 15th Int. Conf. on Fundamental Approaches to Software Engineering, pp.425-438, 2012. ,
C4.5: Programs for Machine Learning, 1993. ,
A survey of decision tree classifier methodology, IEEE Transactions on Systems, Man, and Cybernetics, vol.21, issue.3, pp.660-674, 1991. ,
DOI : 10.1109/21.97458
Regression testing minimization, selection and prioritization: a survey, Software Testing, Verification and Reliability, vol.18, issue.2, pp.67-120, 2012. ,
DOI : 10.1109/ICST.2009.12
Decision trees: Equivalence and propositional operations, 10th Netherlands/Belgium Conf. on AI (NAIC), pp.157-166, 1998. ,
FINDING SMALL EQUIVALENT DECISION TREES IS HARD, International Journal of Foundations of Computer Science, vol.37, issue.02, pp.343-354, 2000. ,
DOI : 10.1145/129617.129621