SESSION

A Score for Pull Request Complexity – Its Impact on Cycle Time and How We Reduced it with AI

A shorter pull request (PR) cycle time is essential for improving developer experience, but too often, pull requests are too complex, touch too many files, and require too many iterations to be quickly and thoroughly reviewed by a peer. The analysis of our data at Atlassian indicates that this results in longer PR cycles and release time.

In this session, we’ll introduce the PR Complexity Score, how we calculate it, and how it helps identify PRs that should be reworked before being submitted for review.

We’ll share how we make its value prominent and explain its meaning within the context of a pull request as part of a recent project we ran. Taking it a step further, we will illustrate how AI can assist by suggesting ways to simplify the changes.

Achieving faster approval for PRs is possible, and optimizing release time will be beneficial for everyone!

Meet the Speakers

Caterina Curti

Caterina is a Developer Advocate at Atlassian, focused on helping developers build apps that add functionalities to Atlassian products. When she is not working, you can find her admiring the Australian ocean and beaches or playing with a dog.

Chris Williams

Chris is a Senior Software Engineer at Atlassian, working on developing the fundamentals of the app ecosystem that expands functionality of various Atlassian products such as Jira and Confluence. He takes an active interest in development best practices and their effects on productivity and reliability.