Exact(60)
We use a random binary number generator to generate test data.
In order to generate test data, some generators such as random test data generators, data specification generators and path-oriented (Path-Wise) test data generators are employed.
Generate test cases from B implementation modules: since B implementations represent more closely the tested code, the ability to also generate test cases from them would reduce the abstraction gap and make the process of refinement of the test cases easier.
The obtained Petri net models are used in order to generate test scenarios.
The approach they present helps to generate test data which take the system to such conditions.
The TConfig tool can generate test cases based on strengths varying from 2 to 6.
The main objective of testing is to generate test data uncovering faults in software modules.
For instance, the works found in the literature does not generate test sets to satisfy both mutation and pairwise testing.
Evaluation criteria and metrics were: For which inputs the tool was not able to generate test cases?
Some of the test formulas contain contradictions that make it impossible to generate test data that satisfy them.
This paper presented a novel CIT algorithm, called TTR, to generate test cases specifically via the MCA technique.
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