On Reducing Test Data Volume for Circular Scan Architecture Using Modified Shuffled Shepherd Optimization

In this manuscript, a novel test data compression (TDC) system is proposes for reducing a test data volume (TDV) for circular scan (CS) architecture. A modified version of meta-heuristic population based optimization approach, hence it is called shuffled shepherd optimization (SSO) and it is used to optimize the conflicting bit minimization (CBM) problem. In CS framework, TDC is reached by upgrading only the conflicting bits among template pattern, real test pattern. Reduced test data volume and test application time are achieved by diminishing the Hamming distance between the currently captured response and the subsequent test vector. The CBM issue is formulated by a traveling salesman problem (TSP). Here, the test vectors are assumed by cities, the HD among test vectors a pair is assumed by distance of interurban. A modified version of the SSO algorithm called as MSSO is applied in combination using mutation operator for solving the issue of CBM. Experimental outcomes display the proposed TDC method using MSSO achieves an average development of 8.36% in compression ratio (CR) as well as 6.77% in TAT is attained by reducing a TDV. This proposed approach outperforms other state-of-art test data compression schemes by providing improved CR, TAT reduction and TDV reduction.