scoss 0.0.2

A Source Code Similarity System

scoss

A Source Code Similarity System - SCOSS

There are four supported metrics:

• count_operator: A metric that counts operators in source-code to calculate similarity score.
• set_operator: A metric that checks the presence of operators in source-code to calculate similarity score.
• hash_operator: A metric that uses the combination of adjacent operators to calculate similarity score.
• SMoss: A wrapper of MOSS (the same as mosspy).

Installations

This package requires python 3.6 or later.

pip install scoss

Usages

You can use SCOSS as a Command Line Interface, or a library in your project, or web-app interface

Command Line Interface (CLI)

Comming soon...

Using as a library

1. Define a Scoss object and register some metrics:

from scoss import Scoss
sc = Scoss(lang='cpp')
# only show pairs that have similarity score > threshold
sc.add_metric('count_operator', threshold=0.7) 
sc.add_metric('set_operator', threshold=0.5)

2. Register source-codes to defined scoss object:

sc.add_file('./tests/data/a.cpp')
sc.add_file('./tests/data/b.cpp')
sc.add_file('./tests/data/c.cpp')
# or add by wide-card
sc.add_file_by_wildcard('./tests/data/problem_A_*.cpp')

3. Run Scoss and get results:

sc.run()
# filter results by combine thresholds from different metrics (and_threshold)
print(sc.get_matches(and_thresholds=True))

The same behaviours is defined in SMoss. You can create SMoss object to use MOSS system.

Web-app interface

Please check our web-app interface here.

Issues

This project is in development, if you find any issues, please create an issue here.

Contributors

Ngoc Bui, Thai Do, Tran Vien.

Acknowledgements

This project is sponsored and led by Prof. Do Phan Thuan, Hanoi University of Science and Technology.

A part of this code adapts this source code https://github.com/soachishti/moss.py as baseline for SMoss.