An Automatic Test Pattern Generation (ATPG) tool is presented that generates compact test sets that test concurrently the digital embedded cores in a System on Chip. The approach is driven by novel graph theoretic problem formulation to generate patterns for two or more cores in parallel. Pairs of input lines from different cores as well as pairs of output lines are systematically allocated on the same Test Access Mechanism (TAM) lines to improve the efficiency of the ATPG. The approach enables core integrators to determine which pairs of cores can be tested concurrently with the same test bus. Low application time for 100% single stuck-at fault coverage is sought subject to a given TAM bandwidth. The experimental results show drastic reductions in the test application time over the conventional ATPG method that generates tests for each core separately.
A complete function-based scheme is presented to identify at-speed sequentially untestable path delay faults. We introduce signature variables to implicitly track error propagation through combinational and sequential circuits. The path sensitization test functions are encoded with the signature variables. These encoded test functions allow implicit identification of all propagating transitions corresponding to each individual test function minterm. We then utilize the signature variables during the fault propagation in a way such that the latched error propagates robustly to an observable point irrespective of other latched errors. Results presented on the ISCAS'89 benchmarks show a large number of sequentially untestable path delay faults are identified.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.