A Simulation-Based Test Generation Scheme Using Genetic Algorithms

This paper discusses a Genetic Algorithm-based method of generating test vectorsfor detecting faults in combinational circuits. The GA-based approach combines the merits of two techniques that have been used previously for generating test vectors - the directed search approach and the random test method. We employ a variant of the traditional GA, the Adaptive GA ( A G A ), to improve the eficacy of the genetic search. Two cost functions that are used for assessing the quality of the vectors are discussed. The performance of the AGA-based test generation approach has been evaluated using ISCAS-85 benchmark circuits, In our approach, the number of vectors that need to be simulated for detecting all detectable faults is significantly smaller than that required for a random test method. Even when optimized input distributions are used to generate the random test vectors, the A G A sustains its superior performance over the random test method.

• Type: Conference
• Year: 1993
• Where: VLSID
• Authors: M. Srinivas, Lalit M. Patnaik
• Keywords: Random Test Method, Random Test Vectors, Test Vectors, VLSI, VLSID 1993