Research on adaptive feedback test vector generation method

Abstract

Self-feedback test vector generation uses the circuit itself to generate test vectors, which greatly reduces the cost of testing without relying on other equipment. However, there are a great number of feedback nodes in the circuit, so how to select the feedback scheme is a problem. This paper proposes an adaptive matching method to select the self-feedback scheme. First, the final feedback nodes are selected by using the self-defined test vector similarity in the adaptive matching method, and then the optimal arrangement order of feedback nodes is determined by using the self-defined test vector matching degree. The self-feedback structure of the sequential circuit is improved and the number of multiplexers (MUXs) is reduced. The test vector similarity and the test vector matching degree are introduced into the parameters TR and Cr of the Spider Wasp Optimization Algorithm (SWO), respectively, so that the parameters can be adaptively adjusted in the process of selecting feedback nodes.