A methodology for controlling the size of a test suite
ACM Transactions on Software Engineering and Methodology (TOSEM)
Data flow testing as model checking
Proceedings of the 25th International Conference on Software Engineering
Generating Efficient Test Sets with a Model Checker
SEFM '04 Proceedings of the Software Engineering and Formal Methods, Second International Conference
Practical Model-Based Testing: A Tools Approach
Practical Model-Based Testing: A Tools Approach
Model-based test prioritization heuristic methods and their evaluation
Proceedings of the 3rd international workshop on Advances in model-based testing
Redundancy based test-suite reduction
FASE'07 Proceedings of the 10th international conference on Fundamental approaches to software engineering
Simulated Satisfaction of Coverage Criteria on UML State Machines
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
Efficient Reduction of Model-Based Generated Test Suites through Test Case Pair Prioritization
MODEVVA '10 Proceedings of the 2010 Workshop on Model-Driven Engineering, Verification, and Validation
Regression testing minimization, selection and prioritization: a survey
Software Testing, Verification & Reliability
Model-based coverage-driven test suite generation for software product lines
Proceedings of the 14th international conference on Model driven engineering languages and systems
| Hi-index | 0.00 |
During the development and maintenance of software, the size of a test suite often increases to such an extent that the costs allocated for its execution are exceeded. In this case, the test suite needs to be reduced. A number of approaches address the problem of test suite reduction. Most of them consider the removal or merging of test cases. However, less attention has been paid to the identification of test cases that are suitable for merging. In this paper, we present a novel approach to fill this gap. Using this approach allows for the identification of test case pairs that, when merged, have a high potential for test suite reduction. We show that two test suites reduced by our approach are considerably smaller in size than those, whose merged test cases were selected randomly. Additionally, we examine the effect of composite test goals on the reduction ratio.