A new test data compression scheme for circular scan architecture is proposed in this paper. A stochastic heuristic based bio-inspired optimization approach namely ant colony algorithm (ACO) is applied after modification and customization to improve compression efficiency. In circular scan architecture, test data compression is achieved by updating the conflicting bits between the most recently captured response and test vector to be applied next. The quantity of conflicting bits also manifests the Hamming distance between the most recently captured response and the next test vector. A significant reduction in test data volume and test application time is achieved by reducing Hamming distance. The problem is renovated as a traveling salesman problem (TSP). The test vectors are presumed as cities and Hamming distance between a pair of test vectors is treated as intercity distance and a modified ACO algorithm in combination with mutation operator is applied here to resolve this combinatorial optimization problem. The experimental results confirm the efficacy of this approach. An average improvement of 6.36% in compression ratio and 4.77% in test application time is achieved. The exhibited technique sustains an optimal level of performance without incurring any extra DFT (design for testability) cost.

中文翻译：

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一种基于改进蚁群元启发式的环形扫描架构的高效VLSI测试数据压缩方案

本文提出了一种新的圆形扫描结构的测试数据压缩方案。一种基于随机启发式的仿生优化方法，即蚁群算法（ACO）在修改和定制后被应用以提高压缩效率。在循环扫描架构中，测试数据压缩是通过更新最近捕获的响应和接下来要应用的测试向量之间的冲突位来实现的。冲突位的数量还体现了最近捕获的响应和下一个测试向量之间的汉明距离。通过减少汉明距离，可以显着减少测试数据量和测试应用时间。该问题被重新设计为旅行商问题 (TSP)。测试向量被假定为城市，一对测试向量之间的汉明距离被视为城际距离，这里应用改进的 ACO 算法结合变异算子来解决这个组合优化问题。实验结果证实了这种方法的有效性。压缩比平均提高 6.36%，测试应用时间平均提高 4.77%。所展示的技术可维持最佳性能水平，而不会产生任何额外的 DFT（可测试性设计）成本。实现了 77% 的测试应用时间。所展示的技术可维持最佳性能水平，而不会产生任何额外的 DFT（可测试性设计）成本。实现了 77% 的测试应用时间。所展示的技术可维持最佳性能水平，而不会产生任何额外的 DFT（可测试性设计）成本。