Tag Archives for community metrics

5 reasons to have a Software Development Community Dashboard

Community managers spend their time in numerous community activities related with his/her main role: to get people to talk and contribute, react to the community managed, keep people engaged, etc. Key Performance Indicators (KPIs) should be set for each community based on its goals. It’s part of the job to elaborate reports with multiple metrics on community health for example. But, measuring should be an effective task.

Keeping this in mind, I’d like to share with you 5 reasons about why community managers or any other professional related with software development should have a dashboard that provides all the data about the community or project that she/he manages:

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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.

Code review is a very important process to improve the quality of the final product, but it can also be very time-consuming, and impose too much effort on the reviewers and the developers themselves. Therefore, when a few people in the Xen Project detected an apparent increase in the number of messages devoted to code review, they become concerned. They decided to use the services of Bitergia to determine what was happening, and how it could impact the code review process of the project. And the report “Code review process analysis in the Xen Project” was born.

Time-to-merge in Xen, per semester

Time-to-merge in Xen, per semester

The main objective of the analysis (composed of two stages) was to verify if this apparent increase was really related to the code review process, and to study other parameters to determine if the code review process was deteriorating in some way. The first stage has already been completed, with three key findings:

  • Time-to-merge, probably the most important parameter to express the toll that a project is paying for reviewing code, is under control. Time-to-merge is counted from the moment a change is proposed, to the moment that change is merged, after running its corresponding code review.
  • Time-to-merge increased from 2012 to the first semester of 2014, running from about 15 days (for 75% of the changes), to close to 30 days. But since then, time-to-merge has decreased: 28 days in the second semester of 2014, and 20 in 2015 (again, for 75% of changes).
  • The trend of time-to-merge is similar despite the size of the change. The same trend is observed for changes composed of one, two, three, four or more than four patches (individual components of a change).

Currently, the second stage of the analysis is being performed. It is expected that this stage will produce actionable dashboards with detailed information that will allow to track in detail the main parameters of the Xen code review process.

These findings and more will be shown in our talk at OSCON. Remember that we will be exhibiting there and you can get a discount using BITERGIA25 code… Don’t miss the chance to visit us there!

OSCON 2016

Metrics to track a FOSS project

So you decided to use metrics to track your free, open source software (FOSS) community. Now comes the big question: Which metrics should I be tracking? The post “Top five open source community metrics to track” that I wrote for OpenSource.com deals exactly with answering that question.

activity-metrics

Based on our experience at Bitergia, the post proposes five families of metrics: activity, size, performance, demographics, and diversity. I’m sure that some important aspects may be missing, but still, this could be your first list of metrics to track, should you be interested in knowing about how your pet project is behaving. Go and read the full post if you are interested in more details.

Efficiency analysis in the OpenStack community Liberty release

Liberty is the new release of OpenStack. This shows an increase in activity and people participating in the development of OpenStack.

  • There are 25,268 commits in total merged into master thanks to the work of 1,873 different developers.
  • In order to have that code into master, it was necessary the effort of 2,239 people that submitted at least one patchset to Gerrit. That means that 83% of them are actual contributors of Liberty release.
  • In terms of community, Launchpad activity shows that 9,919 people helped participating in the bug tracking process, opening, commenting and closing tickets.
  • The mailing lists are a busy channel of communication with 1,742 participants, but IRC seems to be the preferred channel with more than 6,000 detected nicknames.
  • Ask.openstack.org is also an interesting communication channel where there have been 1,386 people participating and around 2,200 different questions.

As a disclaimer, this post will not focus on organizations participating in the OpenStack development, but in the software development process. Organizations information can be easily retrieved in the Activity Board. We believe that process in the OpenStack community is important and even more when we are talking about a team of more than 2,000 different contributors.

Efficiency of the community closing changesets

As mentioned, there have been more than 2,200 people in Liberty release that aimed at contributing with a patchset in the OpenStack community. And only a subset of those pieces of code were eligible to be part of the project and merged into master. However, not all of the people that were part of the that set were even reviewed. Each quarter, the community leaves around a 20% of the changesets population open. This can be observed in the following chart. The y-axis represents the percentage of changesets that were closed (abandoned or merged) per quarter (x-axis).

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Mid Liberty Release Cycle: OpenStack Quarterly Report

Finally we released a new version of the OpenStack Quarterly report. This is intended to provide insights about the software development process of the OpenStack projects. This covers information from several data sources such as Git, Launchpad, Gerrit, Mailing lists, ask.openstack.org and IRC channels. And it aims at providing quantitative and qualitative information about the activity, community and software process.
The executive summary of the document is as follows:
  • Users community keeps growing. With an increase of more than a 300% in the total number of questions posted in ask.openstack.org, this is the unique communnication channels with such measured increase. Other channels such as IRCor mailing lists also grow but slower. Although this is the activity measured for the last year, the last quarter shows a significant activity drop.
  • Active Core Reviewers are increasing. Although mid-release cycle analysis usually show drops of activity in most of the areas, the total number of active core reviewers has reached a new peak. Up to 339 core reviewers participated in the review process. This shows an increase of around 9% if compared to the previous quarter analysis.
  • Process keeps stable. The time to merge patches for the main projects show similar numbers than in previous quarter. However, Nova seems to be the project out of the common time to review with up to 10 days. On the other hand, Glance is more in line with the rest of the projects if compared to previous quarter. In any case, Glance shows the second highest meadian time to review with up to 7 days.
  • IRC activity recovers old activity. Due to unknown issues, the total logs analyzed in the last two previous quarters indicated a huge drop of activity. However, last analysis on this data source shows activity in line with previous quarters. Although this is still an unknown issue, the IRC activity has recovered expected activity.

Project teams are also covered in this quarterly report. This quarterly report follows the Governance file for projects, but ignores specs files. Previous versions of the quarterly report such as 2015-Q1 or 2014-Q4 divided projects into the integrated project, specs, clients and others, with specific sections.

This study can be replicated using the databases available for the OpenStack project and the tag 15.02 of the GrimoireLib library that allows to query those databases.

Kilo: the new OpenStack release

[Updated results based on methodological changes]

Kilo, the new OpenStack release, shows a continuous increase of activity if compared to Juno. From Icehouse to Juno, there was an increase of 6.22% in the number of commits and 17,07% in the number of unique authors. From Juno to Kilo, there’s a higher jump in terms of commits (11,23%) and a lower increase in terms of authors (11,16%). However, with this increase, there is a new peak in the number of unique authors contributing to the OpenStack Foundation projects with close to 1,600 different people participating in its development.

After the continuous increase of activity from release to release that we observed in the past, Kilo, the latest release of OpenStack is showing some stabilization. The differences  between Juno (the previous release) and Kilo are the lowest in the history of the analysis we’ve performed for the OpenStack Foundation. Although this release has reached a new peak in contributors, close to 1,500 different persons, the increase from Juno to Kilo was of around 900 commits and 200 authors while from Icehouse to Juno it was of  700 commits and 70 developers.

The list of organizations participating in the development of OpenStack keeps growing as well: close to 170 different organizations have contributed with at least one commit to the development of Kilo.

As the top ten contributors, we find the following organizations:

companies-contributions-updated

Regarding to the community itself, the timezones analysis shows a widespread activity around the world. OpenStack is a truly 24 hours-a-day continuous development community. There are three main groups of activity: America, on the left side of the chart, Europa/Africa in the center and Asia, on the right.

Total commits by timezone as detected in Git repositories

Total commits by timezone as detected in Git repositories

Ignoring the UTC 0 activity, that may be biased by developers using UTC 0 as their timezone with independence of their point of residence, the rest of the activity shows North America East and West coasts as the main contributors in number of commits. Europe/Africa is quite close to this activity (most of it due to Europe), although biased by the UTC peak of activity. India could be represented by the the small peak in UTC+5, and finally the rest of Asia, with China and Japan in first place, which is consistent with the localization of some contributing companies.

Methodological notes:

  • Some of the repositories under the OpenStack project have been removed of the analysis. As an example, specification projects are not counted for this analysis. The full list of repositories is available at the last quarterly report sponsorized by the OpenStack Foundation.
  • Developers are counted as the actual authors of the piece of code merged into upstream.
  • The time of commit takes into account the time when that piece of code is merged into upstream.
  • Each release, new repositories are added to the list of analyzed projects. This partially explains the continuous increasing activity in the OpenStack Foundation projects.

Data, data and data about your favourite community: GrimoireLib

[This post is part of the lightning talk presented at FOSDEM 2015. The talk was titled as “Data, data and data about your favourite community” whose slides are available in the Bitergia’s Speakerdeck place. The ipython notebook used for visualization purposes is accesible through nbviewer and can be downloaded in GitHub. This is a basic introduction to GrimoireLib.]

GrimoireLib aims at providing a transparency layer between the database and the user. This helps to avoid the direct access to the databases while providing a list of available metrics.

This is a Python-based library and expects an already generated database coming from some of the Metrics Grimoire tools. CVSAnalY, MailingListStats, Bicho and most of the tools are already supported by this library.

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