https://github.com/cqfn/veniq

Veniq uses Machine Learning to analyze source code, find possible refactorings, and suggest those that seem optimal

https://github.com/cqfn/veniq

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.3%) to scientific vocabulary

Keywords

machine-learning refactorings static-analysis
Last synced: 5 months ago · JSON representation

Repository

Veniq uses Machine Learning to analyze source code, find possible refactorings, and suggest those that seem optimal

Basic Info
  • Host: GitHub
  • Owner: cqfn
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 772 KB
Statistics
  • Stars: 20
  • Watchers: 5
  • Forks: 3
  • Open Issues: 23
  • Releases: 0
Topics
machine-learning refactorings static-analysis
Created over 5 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License

README.md

Introduction

Almost every developer would be glad to delegate their routine tasks. Technical debt is the kind of routine we usually do not have time to do. Leaving technical debt may help product development in the short term, but can ruin the project in the long term.

A Long Method code smell and its Extract Method refactoring are among most popular refactorings developers do. However, there is no consensus how to do Extract Method exactly.

In our research project we are aimed to create an Extract Method recommender system using Machine Leanning. The system takes in a source-code of a Java method and recommends how decompose it into two parts.

We are interested in study factors inluencing how developers prefer to do Extract Method refactoring.

Owner

  • Name: CQFN
  • Login: cqfn
  • Kind: organization
  • Email: team@cqfn.org

Code Quality Foundation

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 444
  • Total Committers: 9
  • Avg Commits per committer: 49.333
  • Development Distribution Score (DDS): 0.658
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Evgeny Maslov l****r@g****m 152
Yaroslav Kishchenko y****o@g****m 119
Vitaly Protasov i****o@y****u 109
Katya Garmash k****a@L****m 27
Katya Garmash k****h@g****m 15
Ekaterina Garmash WX5328958 e****h@h****m 13
Anton a****v@g****m 5
Alexander Iovlev a****v@g****m 2
Alexander Iovlev a****v@h****m 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 75
  • Total pull requests: 112
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 6
  • Total pull request authors: 7
  • Average comments per issue: 0.43
  • Average comments per pull request: 0.53
  • Merged pull requests: 64
  • Bot issues: 0
  • Bot pull requests: 14
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • lyriccoder (19)
  • aravij (12)
  • KatGarmash (4)
  • Vitaly-Protasov (2)
  • acheshkov (1)
  • portlek (1)
Pull Request Authors
  • lyriccoder (22)
  • aravij (18)
  • KatGarmash (5)
  • Vitaly-Protasov (5)
  • dependabot[bot] (5)
  • dependabot-preview[bot] (5)
  • aiovlev (2)
Top Labels
Issue Labels
bug (11) enhancement (3) documentation (1)
Pull Request Labels
dependencies (10) bug (1)

Dependencies

.github/workflows/ci.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
requirements.txt pypi
  • beautifulsoup4 ==4.8.2
  • bs4 ==0.0.1
  • cached-property ==1.2.0
  • cchardet ==2.1.6
  • deprecated ==1.2.10
  • flake8 ==3.7.9
  • javalang ==0.13.0
  • lxml ==4.5.0
  • matplotlib ==3.2.1
  • mypy ==0.770
  • networkx ==2.4
  • pandas ==1.1.2
  • pebble ==4.5.3
  • tqdm ==4.32.1
  • typing-extensions *
  • wheel >=0.30.0
setup.py pypi