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Source Code Analyzing Maching is an application for the analysis of similarities between source code files. Currently with Python, Java, C, and C++ file checking capabilities.

Project description

Source Code Analyzing Machine

GitHub Repo Link

  • A locally run application that demonstrates different matching algorithms
  • Current release compares files as a one to one connection
  • Outputs given percentage of similarity and highlighted visualization of the matching sections of input documents
  • Supports C, C++, Java, and Python files

Getting Started

Install PySide2: pip install scam

Run from directly outside source directory: python3 ./source/scam.py

Getting Started

STEP 1

it is recommended to create and navigate to virtual environemnt using python to run script

python3.8 -m venv <dir> 
source <dir>/bin/activate

STEP 2

install source_analyzer python package from Python Package Index. Note: must be running python version 3.8 or greater

pip install scam
OR

Download the latest built compressed file release from source_analyzer-X.X.X.tar.gz

then install downloaded file

pip3 install /<path_to_file>/scam-0.0.2.tar.gz

STEP 3

(make sure xlaunch is running) run script

scam

Known Errors/Issues

Issues- Python files featuring a heavy amount of print statements may cause skewed data.

Project Group: Codalyzers

  • Djoni Austin | @dcaust1n
  • Jared Dawson | @lukinator1
  • Shane Eising | @seising99
  • Julian Marott | @jmmoratta

References:

https://theory.stanford.edu/~aiken/publications/papers/sigmod03.pdf

Project details


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scam-0.3.4.tar.gz (25.0 kB view details)

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  • Download URL: scam-0.3.4.tar.gz
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  • Size: 25.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
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  • Download URL: scam-0.3.4-py3-none-any.whl
  • Upload date:
  • Size: 141.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.3

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SHA256 5747a4b74760f0cf773bf102160f66e304b7dfb5a55d49e95daf77a5a4d91433
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