Analyzing code review in Xen

The Xen project is an open source software project that does pre-commit peer code review. This means that every change to the source code follows a code review process, in which any developer can participate, before being accepted in the code base. During that process, the patch is carefully inspected and improved thanks to the contributions of the reviewers. The process takes place in the xen-devel mailing list.

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Some developers are more equal than others

In a large free, open source software development community, not all developers are equal. Some are more experienced, some are better known, some know better how to adhere to the uses and customs of the project, some write code that is more easily accepted by others. One of the areas where these differences are more noticeable is the code review process. It is not equally easy for all developers to push their patches through code review. Even when the process itself tries to be fair and unbiased, well, “all developers are equal, but some are more equal than others”.

openstack-gerrit-db

Fortunately, we have plenty of data in the code review system. We can use analytics on that data to learn about how difficult it is for developers to get their patches accepted. We will use a OpenStack code review dashboard, composed with data from the OpenStack Gerrit instance to illustrate the process.

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Understanding the code review process in OpenStack

As a part of our tests with Kibana and Elasticserch as frontends for our MetricsGrimoire databases, we’ve set up a dashboard for understanding the code review process in OpenStack (be sure of visiting it with a large screen and a reasonable CPU, otherwise your experience may be a bit frustrating).

Screenshot from 2015-10-22 00-24-53This dashboard includes information about all review processes (changesets) in OpenStack, using information obtained from their Gerrit instance. For each review, we have information such as the submitter (owner), the time it was first uploaded and accepted or abandoned, the number of patchsets (iterations) needed until it was accepted, and the time until it was merged or abandoned. With all of them we have prepared an active visualization that allows both to understand the big picture and to drill down looking for the details. Follow on reading to learn about some of these details.

[Note: this is our second post about our dashboards based on Kibana. If you’re interested, have a look at the first one, about OpenStack code contributions.]

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Behind the big numbers on the Wikimedia code review process

Having a dashboard usually opens new paths to understand software development communities. This may be seen as the entry point that helps to understand the basics of a community. And on top of this, there may appear new questions related to those basics or to more advanced issues. This is the case of the new work we are working on with the Wikimedia community metrics analytics team: Core Reviewer and Participants.

  • Core reviewers are defined as those developers that can exercise a +2/-2 review in Gerrit. In addition to this, it is of interest for the community to remove auto merges. Although this is an undesired behaviour, that takes place, and those should be removed.
  • On the other hand, Participants in Gerrit are defined as any member leaving any type of trace in the system. In this set we can find reviews (-2,-1,+1,+2), uploads, comments and others.

It is interesting to notice that depending on the community, requirements are slightly different. In the case of the OpenStack community, there are extra requirements for the Core Reviewer definition. And this is that reviews should be found in master branch. This specific measure can be found in the OpenStack quarterly reports for each of the projects of the Foundation.

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