Hybrid ATPG (Automatic Test Pattern Generation) algorithm

The project "NN-for-ATPG" proposes a hybrid approach for
Automatic Test Pattern Generation (ATPG) by integrating machine learning
with the FAN algorithm. It includes implementations of two approaches,
NN-Hyb and NN-All. It features two implementations, NN-Hyb and NN-All,
which apply neural network models at selective and all circuit levels,
respectively. Project files support the paper by providing the source
code, circuit files, and scripts needed to reproduce key results,
including comparisons for "all fault cases,"
"hard-to-detect faults," and runtime comparisons with and
without acceleration. Minimal requirements include a C++ compiler and
shell script execution capabilities.