Paper Info
Title
Genetic algorithm based approach for segmented testing
Abstract
Segmented testing, in which a set of test patterns are partitioned into several segments, has been shown to be applicable for on-line testing as it can shorten the mean time to fault detection. One problem that exists for segmented testing is how to partition the set of tests so that the detection latency can be minimized. In this paper, we first propose a method to compute a lower bound of detection latency. Then we present a genetic algorithm (GA) based procedure to partition a given test set into several test segments aiming to reduce the detection latency. Experimental results on ISCAS'89 benchmark circuits demonstrate that the proposed approach can effectively reduce detection latency.
Year
DOI
Venue
2011
10.1109/DSNW.2011.5958841
DSN Workshops
Keywords
Field
DocType
fault detection,on-line testing,integrated circuit testing,integrated circuit reliability,segmented testing,test pattern,iscas89 benchmark circuits,ga-based procedure,detection latency,test patterns,online testing,genetic algorithm,benchmark circuit,genetic algorithms,test segment,benchmark testing,mean time,reliability,testing,lower bound,upper bound
Computer science,Upper and lower bounds,Fault detection and isolation,Latency (engineering),Algorithm,Real-time computing,Electronic circuit,Partition (number theory),Genetic algorithm,Benchmark (computing),Test set
Conference
ISBN
Citations 
PageRank 
978-1-4577-0373-7
2
0.38
References 
Authors
7
5
Name
Order
Citations
PageRank
Xiaoxin Fan1393.86
Sudhakar M. Reddy25747699.51
Senling Wang3185.91
Seiji Kajihara498973.60
Yasuo Sato5384.46