We’ve also taken it a step further and automated part of the work for you with our WorkerB bot. Now you can use your pull request data to see where you stand against industry standards and which areas need focus to help your team deliver on promises and ship features faster. Want to learn more about being an elite engineering team? Check out this blog detailing our engineering benchmarks study and methodology. We compiled the data from our study into an engineering benchmarks chart, identifying parameters for dev teams that are elite, strong, fair, or need focus. But you then have to know if your average times are good or bad. It’s great to know what your cycle time is and to even break that down to see coding time, PR pickup time, PR review time, and deploy time. But we believe that metrics alone don’t improve dev teams. You can’t improve what you don’t measure, which is why we aggregate your issues, Git, and release data into one platform. Our data science team at LinearB studied nearly 2,000 dev teams and discovered that the biggest factor contributing to long cycle time is the code review process, specifically around pull request pickup time, pull request review time and pull request size.Ĭheck out this presentation from our CEO Ori Keren: Developers can request reviews from their colleagues and track the build status of their work via PRs.Īdditionally, using pull requests in the code review process enables you as the leader to track your team’s review process as a whole. Pull requests are built on the principles of code review and team collaboration. Why Are Pull Requests Important for Code Review?
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