https://github.com/bambuscontrol/satd-commits-analysis

Supporting sources for analyzing self-admitted technical debt (SATD) and its correlation with changes in lines, files, and the delta of unit complexity within a commit.
https://github.com/bambuscontrol/satd-commits-analysis

Last synced: about 1 month ago
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Supporting sources for analyzing self-admitted technical debt (SATD) and its correlation with changes in lines, files, and the delta of unit complexity within a commit.

• Host: GitHub
• URL: https://github.com/bambuscontrol/satd-commits-analysis
• Owner: BambusControl
• License: apache-2.0
• Created: 2024-01-24T18:08:06.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-02-04T20:54:03.000Z (11 months ago)
• Last Synced: 2024-10-30T15:12:21.933Z (about 2 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 1.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# SATD Commits Analysis

Supporting sources for analyzing self-admitted technical debt (SATD)

and its correlation with changes in lines, files,

and the delta of unit complexity within a commit.

## Source data

Data extraction was performed using the [SATD GIT Extractor](https://github.com/BambusControl/satd-git-extractor) project.

The tool extracts additional data for the [source dataset](https://github.com/yikun-li/satd-different-sources-data) of another SATD study.[^1]

## Initialize Project

> [!NOTE]

> The following instructions are for Windows using [virtual environment](https://docs.python.org/3/library/venv.html).

> The [Python version](./.python-version) is specified for [PyEnv](https://github.com/pyenv/pyenv).

Initialize Python virtual environment.

```shell

python -m venv env

```

Activate the environment.

```powershell

.\env\Scripts\Activate.ps1

```

Install dependencies.

```shell

pip install -r requirements.txt

```

Now you're ready to use the Jupiter notebook in the [src](./src) directory.

[^1]: Li, Y., Soliman, M. & Avgeriou, P. Automatic identification of self-admitted technical debt from four different sources. Empir Software Eng 28, 65 (2023). https://doi.org/10.1007/s10664-023-10297-9