Search Strategy of Large Nonlinear Block Codes

Test pattern compression techniques reduce the amount of transferred data while decompressed pattern flexibility remains high. The flexibility can be measured by the guaranteed number of specified test pattern bits, equal to or greater than the number of care bits in the pattern. This paper addresses the problem of test pattern compression and decompression using nonlinear codes. Test patterns can be encoded using a linear code that leads to an XOR network that decompresses the compressed patterns transferred from a tester. This XOR network can be completed or replaced by a standard (nonlinear) combinational network with substantially improved compression efficiency. The problem of finding the code was formulated as a clique cover problem. This approach's tight throat lies in computational complexity and the needed memory capacity to temporarily retain intermediate results of clique coverage search attempts. The paper proposes a method that substantially reduces the computational time to get a robust nonlinear code with decompression ability. It shows that random search algorithms cannot reach the code parameters obtained by a restricted iterative search proposed in the paper. Additional knowledge concerning the check-bit truth table characteristics was used to avoid unsuccessful investigations. The proposed decompressor schemes have higher efficiency than till now known decompressor constructions. On the other hand, finding other heuristics that provide efficient codes for a broader class of code parameters is challenging than the proposed solution.