Warning

You are now at beta version of CoEdPilot extension. We will release better backend models and more features at the version. The design does not strictly follow the content of the CoedPilot paper. If you have any questions or suggestions, please feel free to raise an issue.

✏️ CoEdPilot

CoEdPilot is a Visual Studio Code extension that features automatic code edit recommendations, proposed by the paper "CoEdPilot: Recommending Code Edits with Learned Prior Edit Relevance, Project-wise Awareness, and Interactive Nature" by Chenyan Liu, Yufan Cai, Yun Lin, Yuhuan Huang, Yunrui Pei, Bo Jiang, Ping Yang, Jin Song Dong, and Hong Mei. Presented at ISSTA'24.

If you are interested in the training and evaluation of the backend models, please refer to the CoEdPilot repository.

🚀 Demo

Note

Please click the image to watch the demo video on YouTube.

⚙️ Functionality

The extension introduces two major features: Edit Locator and Edit Generator.

Edit Locator

Combining a 🔍 file locator (discriminator) model and a 🎯 line locator model. It suggests edit locations according to previous edits and current edit description.

Edit Generator

Based on a single 📝 generator model. It generates replacements or insertions somewhere in the code, from suggested locations or manually selected. It also requires previous edits and current edit description and, in addition, the code to replace.

✨ UI

Overview

• Predicted locations will be displayed as a tree view in the left ⬅️ and also highlighted in the active editor
• Query status will be displayed in the status bar ↘️
• Edit description is accepted in the input above ⬆️

Diff View

Once performing a prediction on a line, a diff view is shown for switching ↔️ or editing ✏️ the prediction result.

🧑‍💻 Usage

1. Edit the code, as our extension will automatically record most previous edits.

2. Run Predict Locations: right-click anywhere in the editor and select it in the menu, or use the default keybinding Ctrl + Alt + L (in MacOS Cmd + Alt + L).

3. Run Generate Edits: select the code to be edited in the editor, then right-click and select it in the menu, or use the default keybinding Ctrl + Alt + E (in MacOS Cmd + Alt + E).

Note

To select code for editing, you can:

• Click recommended locations in the left location list;
• Select part of the code for replacing;
• Select nothing to generate insertion code at the cursor position.

And by default accepting an edit will trigger another location prediction immediately (you can change this in extension configuration).

4. Manually Change Edit Description: right-click and select it in the menu. By default the input box will automatically show at query whenever the edit description is empty.

5. After the model generates possible edits at that range, a difference tab with pop up for you to switch to different edits or edit the code. There are buttons on the top right corner of the difference tab to accept, dismiss or switch among generated edits.

🚧 Beta features:

• Model upgrade from microsoft/codebert-base to salesforce/codet5-large encoder and salesforce/codet5-base;
• The dataset distribution used for model training is more in-distribution with real world editing scenairos.

🛠️ Setup backend model

Method 1: 🐳 Deploy via Docker (recommended 👍)

Important

• This deployment method is not fully tested. Please feel free to raise issues if you encounter any problems;
• MacOS is unable to use MPS acceleration via Docker, hence the following instructions are not applicable to MacOS.
• If you need CUDA acceleration, your system must have an NVIDIA GPU with the correct drivers installed. Install the NVIDIA Container Toolkit.

You can create a Docker image and start a Docker container according to the following steps to isolate the environment and simplify the backend model deployment.

1. Navigate to the root directory of the CoEdPilot-extension project.

2. Create the Docker image (For Linux / Windows with WSL):

   docker build -t coedpilot-extension --build-arg GFW=<bool>  .

   If you are inside Mainland China, set argument GFW to True. If you wish not to use HuggingFace mirror, please remove ENV HF_ENDPOINT="https://hf-mirror.com/" from Dockerfile

3. Start the Docker container

   The default port is 5003, please check the availability of this port:

   • With GPU acceleration (Recommended 👍):

     docker run --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -p 5003:5003 coedpilot-extension

   • Without GPU acceleration (Not recommended 👎):

     With the following command (with 5003 as default port):

     docker run -p 5003:5003 coedpilot-extension

Now, the backend model is up and running. You can proceed to setup the extension to use CoEdPilot-Extension.

After the usage, you may follow the following command to stop and remove the Docker container and image.

5. ⚠️ Stop the Docker container:

   docker stop $(docker ps -a -q --filter ancestor=coedpilot-extension)

   This command stops all running containers based on the coedpilot-extension image.

6. ⚠️ Remove the Docker container:

   docker rm $(docker ps -a -q --filter ancestor=coedpilot-extension)

7. ⚠️ Remove the Docker image:

   docker rmi coedpilot-extension

Method 2: Manual setup

Important

For Windows and Linux using CUDA 11.8, please follow PyTorch official guide to install PyTorch with CUDA before the following steps.

1. Install Python dependencies: Using pip (with Python 3.10):

   pip install -r requirements.txt

   Or using conda :

   conda create -n code-edit
   conda activate code-edit
   conda install python=3.10.13
   python -m pip install -r requirements.txt

2. Download models into the project directory:

   As mentioned before, we respectively prepared 3 models (file locator(including embedding model, dependency analyzer and a regression model), line locator, and generator) for each language. Supported languages are go, python, java, typescript and javascript.

   Execute the following command to automatically download models.

   python download.py

   Models should be downloaded into the following hierarchy:

   edit-pilot/
      models/
            dependency-analyzer/
            <language>/
               embedding_model.bin
               reg_model.pickle
            multilingual/
               locator_model.bin
               generator_model.bin
   

3. Start the backend:

   python src/model_server/server.py

   The backend will start listening on http://localhost:5003 by default. If you want to change the host and port, please modify src/model_server/server.ini.

🕹️ Extension deployment

Note

Always remember to start up backend models before using the extension.

Method 1: Install from VS Code extension store (Recommended 👍)

1. Simply donwload the extension from VS Code Extension Store.
2. Open VS Code settings (press Ctrl + , / Cmd + ,), search for @ext:CodePhilia.co-ed-pilot.
3. Set coEdPilot.queryUrl to the server address, e.g., http://localhost:5003 or http://<SERVER_IP_ADDRESS>:<PORT>.
4. You are all set! Enjoy coding with CoEdPilot extension.

Method 2: Run extension from VS Code development host (for temporary testing and development purposes)

Note

• Require Node.js (version >= 16). If Node.js not installed, please follow Node.js official website to intall;
• Other extensions will be disabled in the development host.

1. In the project root directory, install Node packages:

   npm install

2. Open the project directory in VS Code. Press F5, then choose Run Extension if you are required to choose a configuration. A new VS Code window (the "development host") will open with CoEdPilot extension loaded.

3. You are all set! Enjoy coding with CoEdPilot extension.

Method 3: Package extension as .vsix (for long-term usage)

1. Make sure you have yarn installed.

   npm install -g yarn
   npm install -g vsce

2. Execute the following command in the project root directory:

   yarn package

   This command will generate a .vsix file in the project root directory, based on the package.json file.

3. Open the VS Code command palette (Ctrl + Shift + P / Cmd + Shift + P), then select Extensions: Install from VSIX... and choose the .vsix file generated in the previous step.

4. Open VS Code settings (press Ctrl + , / Cmd + ,), search for @ext:CodePhilia.co-ed-pilot.

5. Set coEdPilot.queryUrl to the server address, e.g., http://localhost:5003 or http://<SERVER_IP_ADDRESS>:<PORT>.

6. You are all set! Enjoy coding with CoEdPilot extension.

✍️ Citation

If you find our work helpful, please consider citing our paper:

@inproceedings{liu2024coedpilot,
  title={CoEdPilot: Recommending Code Edits with Learned Prior Edit Relevance, Project-wise Awareness, and Interactive Nature},
  author={Liu, Chenyan and Cai, Yufan and Lin, Yun and Huang, Yuhuan and Pei, Yunrui and Jiang, Bo and Yang, Ping and Dong, Jin Song and Mei, Hong},
  booktitle={Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis},
  pages={466--478},
  year={2024}
}

❓ Issues

The project is still in development, not fully tested on different platforms.

Welcome to propose issues or contribute to the code.

😄 Enjoy coding!