Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
Generation of Feasible Test Sequences for EFSM Models
TestCom '00 Proceedings of the IFIP TC6/WG6.1 13th International Conference on Testing Communicating Systems: Tools and Techniques
Automated Unique Input Output Sequence Generation for Conformance Testing of FSMs
The Computer Journal
Generation of optimal finite test suites for timed systems
TASE '07 Proceedings of the First Joint IEEE/IFIP Symposium on Theoretical Aspects of Software Engineering
Applying Evolutionary Computation Methods to Formal Testing and Model Checking
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Generation of improved test cases from UML state diagram using genetic algorithm
Proceedings of the 4th India Software Engineering Conference
Transition coverage testing for simulink/stateflow models using messy genetic algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A preliminary general testing method based on genetic algorithms
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
A case study on the use of genetic algorithms to generate test cases for temporal systems
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Formal testing of timed and probabilistic systems
ICTSS'11 Proceedings of the 23rd IFIP WG 6.1 international conference on Testing software and systems
An improved test generation approach from extended finite state machines using genetic algorithms
SEFM'12 Proceedings of the 10th international conference on Software Engineering and Formal Methods
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Generating test data is computationally expensive. This paper improves a framework that addresses this issue by representing the test data generation problem as an optimisation problem and uses heuristics to help generate test cases. The paper considers the temporal constraints and behaviour of a certain class of (timed) finite state machines. A very simple fitness function is defined that can be used with several evolutionary search techniques and automated test case generation tools.