Untitled

import networkx as nx
import pandas as pd
import sqlite3
import re
import matplotlib.pyplot as plt
import numpy as np
import ast
from functions import fill_conditional_seq, program_to_graph

def process_data(ground_truth_file, database_file, output_file):
    # Load the ground truth CSV
    pgms_csv = pd.read_csv(ground_truth_file)
    list_of_programs = pgms_csv['Program_Name'].to_list()
    list_of_identifiers = pgms_csv['Identifier'].to_list()

    # Connect to the SQLite database
    conn = sqlite3.connect(database_file)
    query = f"""SELECT * FROM BRE_LOGIC_TBL WHERE Program_Name IN ({','.join([f"'{p}'" for p in list_of_programs])})"""
    data = pd.read_sql_query(con=conn, sql=query)

    # Process 'Source_Value'
    data['Source_Value'] = data['Source'].apply(lambda x: ast.literal_eval(x)[0] if isinstance(x, str) else x)

    # Create 'Identifier' column
    data['Identifier'] = data[['Program_Name', 'Target_Value', 'Source_Value', 'Children', 'Parents']].astype(str).agg('/'.join, axis=1)

    # Filter data based on identifiers
    data = data[data['Identifier'].isin(list_of_identifiers)]

    # Remove duplicates
    data = data.drop_duplicates(subset=['Identifier'], keep='first')

    # Create 'Actuals' column
    data['Actuals'] = data[['Program_Name', 'Sequence']].astype(str).agg('_'.join, axis=1)

    # Map 'Program_Snippet'
    data['Program_Snippet'] = data['Program_Name'].map(pgms_csv.set_index('Program_Name')['Program_Snippet'])

    # Save to CSV
    data.to_csv(output_file, index=False)

# Example usage
process_data("ground_truth.csv", "app_db_pc.db", "ground_truth.csv")

actuals = pd.read_csv("ground_truth.csv")

conn    = sqlite3.connect(r"my_db.db")
count = 0
for i in list(actuals['Program_Name'].unique()):
    program = i
    # print(program)
    data    = pd.read_sql_query(con=conn, sql=f"""SELECT * FROM BRE_LOGIC_TBL WHERE Program_Name='{program}'""")
    data = data.astype(str)
    data = data.replace("nan", None).replace("None", None)
    data['Conditional_Seq'] = fill_conditional_seq(data)
    data.Sequence = data.Sequence.astype(int)
    data          = data.sort_values(by='Sequence')
    G = program_to_graph(data)
    actual = list(actuals.loc[actuals['Program_Name'] == program, 'Actuals'].values)
    path = list(nx.shortest_path(G, target=str(actual[0])).items())[-1][-1]
    whole_path1 = []
    for i in path:
        whole_path1.append(G.nodes[i]['statement'])
    # print(actuals.loc[actuals['Program_Name'] == program, 'Program_Snippet'].values[0])
    # print(type(actuals.loc[actuals['Program_Name'] =
    if ast.literal_eval(actuals.loc[actuals['Program_Name'] == program, 'Program_Snippet'].values[0]) == whole_path1:
        print()
        print(program)
        print("Passed !!")
    else:
        print()
        print(program)
        print("Failed !!")
    # print(f"Done for File Number : {count}, Name : {program}")
    count = count + 1