Improved SAT-based ATPG: More constraints, better compaction

Automatic Test Pattern Generation (ATPG) based on Boolean Satisfiability (SAT) is a robust alternative to classical structural ATPG. Due to the powerful reasoning engines of modern SAT solvers, SAT-based algorithms typically provide a high test coverage because of the ability to reliably classify hard-to-detect faults. However, a drawback of SAT-based ATPG is the test compaction ability. In this paper, we propose an enhanced dynamic test compaction approach which leverages the high implicative power of modern SAT solvers. Fault detection constraints are encoded into the SAT instance and a formal optimization procedure is applied to increase the detection ability of the generated tests. Experiments show that the proposed approach is able to achieve high compaction - for certain benchmarks even smaller test sets than the currently best known results are obtained.

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