Publication Type:

Journal Article


Communications in Computer and Information Science, Volume 305 CCIS, Kochi, p.84-92 (2012)





Approximate solution, Binary string, Chromosomes, Communication systems, Crossover and mutation, Environmental protection, Fitness values, Genetic algorithms, Genetic operations, Initial population, Input tests, Multiple fault diagnosis, Multiple faults, Optimization, Search problem, Search technique, Switching activities, Test power, Test power reduction, Test vector reordering, Test vectors, Testing, Vectors, VLSI design


In this paper, a novel method for multiple fault diagnosis is proposed using Genetic Algorithms. Fault diagnosis plays a major role in VLSI Design and Testing. The input test vectors required for testing should be compact and optimized .Genetic Algorithm is a search technique to find approximate solutions to optimization and search problems. The proposed technique uses binary strings as a substitute for chromosomes. The chromosomes (test vectors) are initialized randomly and their fitness value is evaluated. Genetic operations selection, crossover and mutation are performed on this initialized set (initial population) to reproduce better test vectors. The test vectors thus generated are reordered by using a reordering algorithm. The total switching activity among the reordered test vectors is thus optimized and hence the reduction of test power. © 2012 Springer-Verlag.


cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@1417ce1 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@726d986b Through org.apache.xalan.xsltc.dom.DOMAdapter@7931d37d; Conference Code:92037

Cite this Research Publication

J. P. Anita and Vanathi, P. T., “Multiple fault diagnosis and test power reduction using genetic algorithms”, Communications in Computer and Information Science, vol. 305 CCIS, pp. 84-92, 2012.