From Engineers For Engineers

The Codalytics Code Review Analytics Tool helps engineering teams to identify improvement areas for their code review practice. It focus on several code review dimensions, most importantly it sheds light on the the code review speed, and the code review value that your team is getting from code reviews.

Data-driven Engineering Insights

Use actual engineering data to understand and improve the code review practices of various teams.

Codalytics helps you answer questions such as:

  • Why are some teams more effective than others?
  • Which code review practices do high-performing teams follow?
  • Are some code reviews rather rushed?
  • What processes do teams follow?

Codalytics is based on the findings of the latest code review research. It highlights code review benefits, such as knowledge sharing, code improvements, bug finding, mentoring and learning within your actual engineering data. Based on the analysis, you can identify the return of investment for your code review strategy.

3 Perspectives - Multiple Insights

Codalytics shows you time, size and participation rate for your code reviews.


Understand the how engineers participate during code reviews. The tools helps to see code review approval practices, knowledge flows, and helps to identify "rubberstamps", i.e., code reviews that haven't been thoroughly reviewed. i.e.

Code Review Speed

Understand how long do code reviews take from start to merge, and how long code reviews with no interaction take. The tools also helps you identify blocked PRs, and track them over time.

Code Review Size

Research has shown that code review size has a significant impact on code review speed, and feedback quality. Codalytics shows you how review size impacts knowledge sharing, and code improvements based for your engineering team.

Want to see it in action?

Join the waiting list to become an early beta user.

The Story Behind Codalytics

Dr. Michaela Greiler worked with all major engineering teams at Microsoft, and many other product teams from companies around the world, to help them improve their engineering practices in a grounded and data-driven way.

While a lot of insights are revealed by talking to engineers, and discussing with them their engineering practice, actual engineering data is crucial to complement this picture.
Traces and patterns within engineering data are an important aspect to understand the behavior or engineers and reveal bottlenecks and improvement possibilities.

In addition, this data has to be analyzed and looked-at with the right mindset and curiosity, that most current analytics tool do not incorporate. It's crucial that the data is not misused to create vanity metrics that give executives or management a false feeling of understanding and control.

That's why this tool is build by engineers for engineers. Michaela designed Codalytics to help reveal what really matters to engineering teams, and to allow them to ask and answer relevant questions to the data, in order to build more cohesive teams and engineering practices.