├── README.md
├── code
│ ├── aiger_tools # Tools for convert .aig
│ ├── bmc.py # Implementation of BMC (used in PDR)
│ ├── config.py # Input parameters
│ ├── data_gen.py # Generate graph from aiger
│ ├── generate_aag.py # convert .aig to .aag
│ ├── main.py # Main function to run PDR in certain aiger files
│ ├── mlp.py # Simple implementation of MLP
│ ├── model.py # Parser for parse .aag into z3
│ ├── neuro_predessor.py # Neural Network model to train and inference
│ ├── pdr.py # Implementation of PDR
│ ├── run_slurm.py # This file could be used when run the program on slurm
│ ├── solver.py # Z3, Minisat (used by PDR)
│ ├── ternary_sim.py # Implemtation of ternary simulation
│ └── train.py # Training file for data processing
├── dataset # Dataset of training and validation
│ ├── Cora
│ ├── Cora2
│ ├── ILAng_pipeline
│ ├── aag4train
│ ├── edgelist
│ ├── eval
│ ├── fuzzing_aig
│ ├── generalization
│ ├── generalization_old
│ ├── generalize_pre
│ ├── hwmcc07_amba
│ ├── hwmcc07_tip
│ ├── tmp
│ ├── toy_experiment
│ └── train
├── deps # Some dependent modules
│ └── PyMiniSolvers
├── log # Contains logs file
│ ├── RL_spec3-and-env.txt
│ ├── hwmcc07_amba_naive.txt
│ ├── neuropdr_no1.log
│ ├── neuropdr_no1_detail.log
│ └── nusmv.syncarb5^2.B.txt
├── model # Model saved after training
│ ├── neuropdr_no1_best.pth.tar
│ └── neuropdr_no1_last.pth.tar
├── requirements.txt # In order to reproduce the experiment environment fast
└── script
└── fetch_info_from_log.py # Generate table from logsdataset folder (hwmcc 07): /data/hongcezh/clause-learning/data-collect/hwmcc07-7200-result/output/tip/eijk.S953.S
dataset folder (hwmcc 20): /data/hongcezh/clause-learning/data-collect/hwmcc20-7200-result/output
aiger size: /data/hongcezh/clause-learning/data-collect/stat/