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The light bulb shadow test followed the standard of ISO/DIS 13564-1 for traveling and maneuvering tests with four test paths (Test Nos. 1, 3, 4, and 6).
In this paper, we introduce a new genetic algorithm for generating test paths.
The number of test paths equals to the cyclomatic complexity of program defined by McCabe.
Finally, we use a trained convolutional network to successfully navigate a Pioneer 3-AT robot on 5 distinct test paths.
These test requirements reflect the inherent connectivity and regularity of each module and, when supported by corresponding hierarchical test paths, they guarantee complete testability of the module.
We discuss a novel method for identifying test requirements of modules in a hierarchical design in order to facilitate the construction of cost-effective hierarchical test paths.
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The results showed that the proposed technique causes substantial reduction in path generation effort, and that the proposed GA algorithm is effective in test path generation.
In essence, they combine the generality required for fast hierarchical test path construction with the precision necessary for minimizing the incurred cost, thus fostering cost-effective hierarchical test.
This paper also presents an approach for the automated generation of feasible independent test path based on the priority of all edge coverage criteria.
Structural equation modeling (SEM) was used to model and test path directionality and magnitude between the latent constructs of social support quality and quantity on risky behaviors.
Only if the test path was precisely 6 times the reference path would fringes be seen.
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CEO of Professional Science Editing for Scientists @ prosciediting.com