80 lines
2.1 KiB
Python
Executable File
80 lines
2.1 KiB
Python
Executable File
#!/usr/bin/env python3
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import javalang
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import os
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import pandas as pd
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import glob
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import tabulate
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# God class if:
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# |M(C)| > E(M) + 6*V(M)
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# (number of methods greater than average across all classes plus 6 times the
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# standard deviation)
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DIR: str = os.path.dirname(os.path.realpath(__file__))
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SOURCES: str = DIR + '/resources/xerces2-j-src'
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OUT_DIR: str = DIR + '/god_classes'
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def clean_output():
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filelist = glob.glob(OUT_DIR + '/*.csv')
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for f in filelist:
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os.remove(f)
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def parse(path: str) -> list[tuple[str, str]]:
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# Get the AST of the file
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with open(path) as file:
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data = file.read()
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tree = javalang.parse.parse(data)
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# Fetch package name from package declaration
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# if node is missing, assuming default package ('')
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package_name = ''
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for _, node in tree.filter(javalang.tree.PackageDeclaration):
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package_name = node.name
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break
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# Get all classes and number of methods for each one
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rows: list[tuple[str, str]] = []
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for _, node in tree.filter(javalang.tree.ClassDeclaration):
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fqdn = package_name + '.' + node.name
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rows.append((fqdn, len(node.methods),))
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return rows
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def create_df(root) -> pd.DataFrame:
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frame = pd.DataFrame(columns=['class_name', 'method_num'])
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i: int = 0
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for path, dirs, files in os.walk(root):
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for f in files:
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if f.endswith('.java'):
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# for each java file, add all entries found to dataframe
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for row in parse(path + '/' + f):
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frame.loc[i] = row
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i += 1
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return frame
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def main():
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clean_output()
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df = create_df(SOURCES)
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mean = df.loc[:, 'method_num'].mean()
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std = df.loc[:, 'method_num'].std()
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threshold = mean + 6 * std
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god_classes_df = df[df['method_num'] > threshold]
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god_classes_df.to_csv(OUT_DIR + '/god_classes.csv')
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god_classes_df.columns = ['Class Name', '# Methods']
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god_classes_df = god_classes_df.set_index('Class Name', drop=True)
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print(god_classes_df.to_markdown())
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if __name__ == '__main__':
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main()
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