CRIS: a test cultivation program for sequential VLSI circuits
ICCAD '92 1992 IEEE/ACM international conference proceedings on Computer-aided design
Genetic Algorithms in Search, Optimization and Machine Learning
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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Automatic test vector cultivation for sequential VLSI circuits using genetic algorithms
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A genetic algorithm framework for test generation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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ISQED '06 Proceedings of the 7th International Symposium on Quality Electronic Design
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Genetic algorithm for test pattern generator design
Applied Intelligence
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Journal of Electronic Testing: Theory and Applications
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Journal of Systems Architecture: the EUROMICRO Journal
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The paper examines the potentialities of genetic algorithms (GAs) with respect to the development of high-level TPGs. It summarizes at first the most relevant test pattern generation techniques based on genetic algorithms (GAs). This analysis distinguishes the considered techniques with respect to the abstraction level of the design under test. In particular, the effectiveness of gate-level GA-based TPGs is compared with the effectiveness of high-level GA-based TPGs. Differences are deeply investigated. They mainly concern the way genetic operators exploit specific simulation information to heuristically guide the genetic evolution. Moreover, a functional testing framework is described and used to actually measure on high-level descriptions the effectiveness of sophisticated GA-based TPGs in comparison to random approaches. Results are reported on a variety of benchmarks.