https://github.com/leriomaggio/code-coherence-evaluation-tool
Django-Admin based web application supporting automatic code analysis, review, and Code/Comments Coherence Evaluation
https://github.com/leriomaggio/code-coherence-evaluation-tool
Last synced: 4 months ago
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Django-Admin based web application supporting automatic code analysis, review, and Code/Comments Coherence Evaluation
- Host: GitHub
- URL: https://github.com/leriomaggio/code-coherence-evaluation-tool
- Owner: leriomaggio
- License: bsd-3-clause
- Created: 2015-11-19T09:11:28.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2022-12-26T20:21:20.000Z (almost 3 years ago)
- Last Synced: 2025-04-08T14:43:11.211Z (6 months ago)
- Language: Java
- Homepage: http://www2.unibas.it/gscanniello/coherence/
- Size: 12.3 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Code Coherence Evaluation Tool
Django-Admin based web application supporting automatic code analysis,
code reading, and code-comments coherence evaluation.
The application has been developed to support the creation of the
[**Coherence Dataset**](http://www2.unibas.it/gscanniello/coherence/),
a publicly available benchmark containing annotated `(code, comments)`
pairs, and their corresponding Coherence evaluation.
# Main Dependencies
The whole code base of the project has been developed in **Python 3**, and in **Django 1.6.x**.
Other dependencies are:
* `celery` and `rabbitmq`: necessary in the code analysis phase, which is activated every time a
new project is uploaded;
* `Antlr3` (included): to support Java Code Analysis
(**Note**: So far, only the analysis of Java code is supported)
# Setup
To setup the entire project, it is required to have a Python environment properly configured
as to satisfy all the package dependencies.
For the sake of simplicity, these dependencies have been collected in the `requirements.txt` file by
the `pip freeze` command.
Thus, to install all the dependencies, it is just required to execute the following command:
pip install -r requirements.txt
To avoid polluting the main system (Python) environment, it is highly suggested to create a
proper *virtual environment* for the specific sake:
venv -p python3
source /bin/activate
pip install -r requirements.txt
## Setup Database
Once the environment has been properly set up, it is finally necessary to create a database
using **PostgreSQL** (`9.3`). For further details on this, please refer to the
[official documentation](http://www.postgresql.org/docs/9.3/static/),
depending on your machine and operating system.
Please refer to the `DATABASES` directive in the *Main Settings*
(`code_comments_coherence/code_comments_coherence/settings.py`) to see the details about
database name and corresponding authentication parameters.
## Restore Database
The code ships with the set of initial data to **re-create** the database from scratch.
The data are provided in the form of `fixtures`, located in the `source_code_analysis/fixture` folder.
This folder contains the `initial_data` archive, and the corresponding instructions to unpack it.
To recreate the entire (*Structure+Data*), it is necessary to execute the following command:
python manage.py syncdb
# Additional Notes
In case it is necessary to upload the source code of **new** software projects, it is required to have
a set of **Celery workers** running on a **RabbitMQ** queue.
To spawn server(s), please take a look at the `RUNNING_Servers.md` file.
# References
A. Corazza, V. Maggio, G. Scanniello, *On the Coherence Between Comments and Implementations in Source Code*,
In Procs of **41st EUROMICRO Conference on Software Engineering and Advanced Applications** (SEAA),
*26-28 Aug. 2015*, Madeira (Portugal) **DOI**: `10.1109/SEAA.2015.20`