Repository | Book | Chapter
(2008) Innovative techniques in instruction technology, e-learning, e-assessment, and education, Dordrecht, Springer.
Np-hard graph problems' algorithms testing guidelines
artificial intelligence principles and testing as a service
Deniss Kumlander
pp. 112-116
There is a permanent great interest in developing fast exact algorithms solving NP-hard problems like finding the maximum clique, a vertex coloring and so forth. The testing step is an essential one in the process of inventing new algorithms and can generate a lot of valuable information if it is built and used appropriately. The paper proposes methods and functionalities that should be included into the testing tool. The high level idea is to use the testing process as a service for the algorithms construction process by providing necessary feedback, i.e. have a concurrent cycle between the algorithm (mathematical) production phase and the testing phase. Thereafter the paper discusses what kind artificial intelligence can be implemented into such testing tool to increase the quality of results and vice versa - what the testing tool can produce for the artificial intelligence algorithms targeted to solve NP-hard problems.
Publication details
DOI: 10.1007/978-1-4020-8739-4_20
Full citation:
Kumlander, D. (2008)., Np-hard graph problems' algorithms testing guidelines: artificial intelligence principles and testing as a service, in M. Iskander (ed.), Innovative techniques in instruction technology, e-learning, e-assessment, and education, Dordrecht, Springer, pp. 112-116.
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