ATPG using Genetic Algorithm

This is the major project work of POOJA, ASHISH, JAGRUTH and SUHAS of The national institute of engineering, Mysuru.

Tools required/ used

• iverilog
• vvp
• python 3.8
  • random
  • pandas
  • numpy
  • subprocess
  • multiprocessing
• MatLab

Discription of files

The folder FullAdders consist of verilog implementation of full adder with single stuck at faults. full_adder0.v is the fault-free and the rest are faulty implementations.

Folder TestBenches contains the test bench implementation of 8-bit excess 3 encoder. test_bench0.v is for fault-free case, rest are for faulty case.

process.py uses shell commands to generate verilog code for each combination of full adder and test bench i.e. Excess 3 encoder. The Folder Results will contain all outputs for each combination in text file format out{test-Bench-code}[{0indicated to full_adder0.v}, {the faulty full adder code}].

TXTtoCSV.py collates all the output text files to a single text files of DATA.txt, this can be used to generate the DATA.csv file and further the transDATA.csv.

transDATA.csv contains the data formated to be used with pandas, use this file for all further processing and don't make changes to this.

The folder genetic_algorithm contains both the genetic algorithm implementation and ATPG testing codes