Aiding Test Case Generation in Temporally Constrained State Based Systems Using Genetic Algorithms

Derderian, Karnig; Merayo, Mercedes G.; Hierons, Robert M.; Núñez, Manuel

doi:10.1007/978-3-642-02478-8_41

Cited by 14 publications

(8 citation statements)

References 6 publications

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“…Derderian et al also applied GA to generate test data for Finite State Machine(FSM) with temporal constraints [8]. The fitness function was based on the number of temporal constraint violations committed by each candidate input sequence.…”

Section: Related and Future Workmentioning

confidence: 99%

Transition coverage testing for simulink/stateflow models using messy genetic algorithms

Harman

Yoo

2011

Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation

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Section: Related and Future Workmentioning

confidence: 99%

Transition coverage testing for simulink/stateflow models using messy genetic algorithms

Harman

Yoo

2011

Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation

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“…Selection of test cases did by mutation analysis. Derderian K. et al [26] presented an approach for GA based test case generation of FSM. Fitness function is based on temporal constraints and guard ranking.…”

Section: Related Workmentioning

confidence: 99%

“…Selection technique proposed in literature for EFSM: [15,16,17,18] proposed the control flow based selection technique and [19, 20 , 21, 22, 23] proposed the data flow selection technique for EFSM based test sequence. node is calculated by using algorithm presented in [26]. We use roulette wheel method for selecting individuals.…”

Section: Related Workmentioning

confidence: 99%

Path Oriented Test Case Generation for UML State Diagram using Genetic Algorithm

Minj¹,

Belchanden²

2013

IJCA

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“…A different line of research in testing of timed systems consists in using genetic algorithms to select better test cases among the (possibly infinite) test cases that can be derived from a given specification [4,5].…”

Section: Other Work On Testing Of Timed and Probabilistic Systemsmentioning

confidence: 99%

Formal Testing of Timed and Probabilistic Systems

Núñez

2011

Testing Software and Systems

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This talk reviews some of my contributions on formal testing of timed and probabilistic systems, focusing on methodologies that allow their users to decide whether these systems are correct with respect to a formal specification. The consideration of time and probability complicates the definition of these frameworks since there is not an obvious way to define correctness. For example, in a specific situation it might be desirable that a system is as fast as possible while in a different application it might be required that the performance of the system is exactly equal to the one given by the specification. All the methodologies have as common assumption that the system under test is a black-box and that the specification is described as a timed and/or probabilistic extension of the finite state machines formalism.

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Aiding Test Case Generation in Temporally Constrained State Based Systems Using Genetic Algorithms

Cited by 14 publications

References 6 publications

Transition coverage testing for simulink/stateflow models using messy genetic algorithms

Transition coverage testing for simulink/stateflow models using messy genetic algorithms

Path Oriented Test Case Generation for UML State Diagram using Genetic Algorithm

Formal Testing of Timed and Probabilistic Systems

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