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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)

See document by passing --help argument.

scoss --help
Usage: scoss [OPTIONS]

Options:
  -i, --input-dir TEXT      Input directory.  [required]
  -o, --output-dir TEXT           Output directory.
  -tc, --threshold-combination [AND|OR]
                                  AND: All metrics are greater than threshold.
                                  OR: At least 1 metric is greater than
                                  threshold.

  -mo, --moss FLOAT RANGE         Use moss metric and set up moss threshold.
  -co, --count-operator FLOAT RANGE
                                  Use count operator metric and set up count
                                  operator threshold.

  -so, --set-operator FLOAT RANGE
                                  Use set operator metric and set up set
                                  operator threshold.

  -ho, --hash-operator FLOAT RANGE
                                  Use hash operator metric and set up hash
                                  operator threshold.

  --help                          Show this message and exit.

To get plagiarism report of a directory containing source code files, add -i/ --input-dir option. Add at least 1 similarity metric in [-mo/--moss, -co/--count-operator, -so/--set-operator, -ho/--hash-operator] and its threshold (in range [0,1]). If using 2 or more metrics, you need to define how they should be combined using -tc/--threshold-combination (AND will be used by default).

Basic command: scoss -i path/to/source_code_dir/ -tc OR -co 0.1 -ho 0.1 -mo 0.1 -o another_path/to/plagiarism_report/

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)
  1. 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')
  1. 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.