Leveraging GPT To Streamline the Pull Request Review Process in Azure Pipelines

More than 11,807^[i] companies are using Azure pipelines as a cloud-based continuous integration and continuous delivery (CI/CD) service. This critical component of the Azure DevOps Services suite is widely used by software development teams to automate the building, testing, and deployment of their applications.

But, what if an application demands code changes?

A Pull Request (PR) review process is a critical part of collaborative software development, especially in version control systems like Git and platforms like GitHub, GitLab, or Azure DevOps. It involves a structured approach to evaluating and discussing code changes proposed in a PR before they are merged into the main codebase.

Even so, this fundamental concept in modern software development, causes various challenges in the Azure Pipelines PR review process. These include manual review effort, review of backlogs, lack of reviewers, inaccurate reviews, communication challenges, code complexity, and more.

Nonetheless, by combating these complexities, businesses can leverage PRs as a way to propose changes to a codebase.

In this blog post, we’ll explain how businesses can leverage the Generative Pre-trained Transformer (GPT) model from OpenAI to review Pull Requests and provide feedback as comments within the PR itself. You’ll also learn how this integration with Azure Pipelines streamlines the PR review process and offers several advantages.

How to Leverage GPT for an Enhanced PR Review Process

1. Reviewing Pull Requests: The GPT Pull Request Review Task can be triggered when an application build is initiated from a pull request. If there’s feedback to provide on the code changes, the task would automatically add comments to the PR. If the build is manually triggered, the GPT Pull Request Review Task could be skipped.

2. Integration/Implementation Steps: Before using the task, ensure that your application build service has the necessary permissions to contribute to PRs in your repository and grant the task access to the system token. The process involves giving permission to the Build Service Agent and updating YAML pipelines.

3. How to Use It:

• Install the Extension: Begin by installing the extension in your Azure DevOps business. Follow the prompts and authorize the extension to access your Azure DevOps account.

• Add the Task to the Build Pipeline: Once the extension is installed, add the “Review Pull Request by GPT” task to your build pipeline.

• Configure the Task: In the task configuration, provide your API key for the OpenAI API. You can also generate an API key on the OpenAI platform.

By implementing the “GPT Pull Request Review Task for Azure Pipelines,” you can enhance the efficiency of your PR review process, reduce manual efforts, and focus on the critical aspects of code functionality. This integration represents a significant advancement in automating your code review process and ensuring coding standards compliance.

To Conclude

The integration of the GPT Review into the PR process brings about various transformative benefits.

• It tackles the time-consuming nature of manual reviews, particularly with a substantial number of files, by significantly reducing the effort required.

• The automation of coding standards management not only enhances efficiency but also saves time.

• The remarkable acceleration in the validation and commenting process, from hours to mere seconds, is a testament to the efficiency gains.

• The complete elimination of manual efforts for coding standards brings about a remarkable 100% reduction.

• While still prioritizing functionality, the GPT Review streamlines the PR review process, reducing efforts by approximately 20%.

Altogether, this approach results in a noteworthy reduction in the overall review time for a single PR, leading to substantial savings in manual efforts.

Ready to Automate Your Code Review and Ensure Coding Compliance With GPT? Let’s Talk!

References:

^[i] Discovery