Automatic test generation using quadratic 0-1 programming
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Advanced Techniques for GA-based sequential ATPGs
EDTC '96 Proceedings of the 1996 European conference on Design and Test
Challenges and directions for testing IC
Integration, the VLSI Journal
Polynomially Complete Fault Detection Problems
IEEE Transactions on Computers
On applying molecular computation to binary linear codes
IEEE Transactions on Information Theory
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Testing of digital circuits is a compute intensive problem. This article deals with the problem of automated test pattern generation for large digital circuits. A new evolutionary approach based on DNA computing is presented, which exploits the computational power of DNA molecules to solve the problem. A Boolean formula in conjunctive normal form is extracted from the circuit under test and then the proposed algorithm based on DNA computing is used to find the solution satisfying that formula. Exploiting the massive parallelism and recombination properties of DNA molecules, a test vector is found in polynomial time i.e., O (nk). Its effectiveness in terms of Fault coverage, CPU time and Test vector generated is compared with some existing classical approaches like simulated annealing and genetic algorithms.