Community metrics

How is the MediaWiki / Wikimedia tech community doing? Let's analyze the data available in order to highlight the contributors and areas setting an example, and also the bottlenecks or inactive corners requiring our attention.

Your feedback and requests are welcome in Bugzilla (product Analytics, component Tech community metrics). You can also comment at the discussion page and at the Analytics mailing list.

Reports
We aim to publish reports interpreting the data obtained on a quarterly basis. Below you can find the initial reports published, based on data retrieved manually.
 * /2013-Q1/ - we are starting doing the reports on a quarter basis.
 * /December 2012/
 * /November 2012/
 * /October 2012/

Metrics dashboard
Under development since June 2013: Updated daily, this dashboard provides data about our Git repositories, Bugzilla, Mailing Lists, Gerrit and IRC. Below you can find the details about what sources are being scanned.
 * http://korma.wmflabs.org/browser/

We are also polishing the data (finding duplicates, assigning contributors to the WMF and other organizations...). If you see any mistake or possibility of improvement please report it.

Powered by Open Source projects Metrics Grimoire and Viz Grimoire. See also the development specific to this dashboard in GitHub. Bugs, enhancement requests and patches for these projects must be submitted directly upstream.

Git
ssh -p 29418 gerrit.wikimedia.org gerrit ls-projects | grep "mediawiki/extensions
 * The source code repos analyzed are mediawiki/core and all the mediawiki extensions:
 * FIXME: This is only a portion (a big one, yes) of all the repositories we need to scan. The default is everything at gerrit.wikimedia.org but let's look at every repo before adding it just in case.

gerrit.wikimedia.org

 * The source code repos analyzed are mediawiki/core and all the mediawiki extensions

bugzilla.wikimedia.org

 * The products analyzed are MediaWiki and MediaWiki extensions
 * FIXME: This is only a portion (a big one, yes) of all the repositories we need to scan. The default is everything at gerrit.wikimedia.org but let's look at every repo before adding it just in case.
 * FIXME - Time to fix graph goes over the roof! (funny, isn't it?)  :)
 * FIXME - Fine tune By repository.

mediawiki.org

 * The wiki activity is analyzed using an analyzer tool including editions, editors and pages. Results and discussion.

lists.wikimedia.org

 * FIXME - mailing lists missing: mediawiki-l, ee, qa... more?
 * FIXME - Is it possible to specify the number of subscribers?

IRC

 * Pending to define the channels to be added to the dashboard.

Contributors
The process to merge users identities from different data sources has three steps: At the end there is a common upeople (unique people) table for all data sources and all data sources map its people table to this common upeople table. Gerrit (SCR) and IRC are not yet supported.
 * unifypeople.py analyzes people in SCM (Git) trying to join identities from the email and the name
 * its2identities.py does the same process for ITS identities (Bugzilla)
 * mls2identities.py does the same process for MLS identities (mailman)

The user pages for Top contributors are linked in the top tables in the metrics browser. For example for SCM the third global committer has his own personal page.

Once unique people exists, other categories are created using it. For example, companies classification is done initially with a script that uses email domains if available. The classification supports periods of time to cover that a unique people has worked for several companies. There is some experimental support also for countries.
 * FIXME - Contributors must be linked to WMF and other orgs.
 * FIXME - Is By country relevant? Do we want to gather that data?
 * FIXME - Plan for linking this data to user profiles? Where?

Other data sources and tools
Git
 * Wikimedia stats in Ohloh including many projects.
 * "How many unique contributors submitted unique pull requests to a https://github.com/wikimedia/ repo" - Python script by marktraceur.

Gerrit
 * Gerrit/Navigation
 * MediaWiki Gerrit stats  (Is it working? 2013-06-28)  and how to query Gerrit data.
 * Number of gerrit committers (marktraceur's bash script)
 * cmd-query for Gerrit.

Bugzilla
 * Bugzilla Weekly Report.

mediawiki.org
 * monthly Statistics of page views and how the data is gathered.

Mailman
 * Wikimedia Mail Stats: PowerPosters.

Key performance indicators
Key factors to watch, in the scope of projects deployed in Wikimedia servers: All this indicators are computed using the databases updated daily.
 * Are the teams more efficient processing contributions?
 * Is the share of non-WMF contributions growing?
 * Are WMF and non-WMF contributions treated equally?
 * Are the attraction and retention of new contributors improving?
 * Are we improving the sustainability of our community?

Who contributes code
Who is contributing merged code each quarter? How is the weight of the WMF evolving? What regions have a higher density of contributors? The evolution of the total amount of merged commits should be visible too. Two charts? What type?
 * Number of developers and commits by organization: Wikimedia (WMF, WMDE...), known companies, OSS projects (if relevant) and independents.
 * Number of developers and commits by country, based on the data provided.

Queries
Reviews Database
 * Basic:


 * Email domains:

Metrics

 * DB updated on 2013-08-22
 * Total revisions: 56127
 * Total abandoned: 3015
 * Total contributors with merged code: 319
 * Total contributors with abandoned code: 263
 * Total organizations with merged code: 108
 * Total organizations with abandoned code: 82
 * Number of revisions merged per contributor
 * Number of revisions abandoned per contributor
 * Number of revisions merged per organization
 * Number of revisions abandoned per organization
 * Ratios merged/abandoned
 * Tops

Analysis

 * Top 10 for contributors: 7 WMF, 3 WMDE.
 * Only one organization has more than 500 merged: Wikimedia (@wikimedia.org + @wikimedia.de): 13593 + 2132
 * Only one organization has more than 300 abandoned: Wikimedia.

Gerrit review queue
'' Changes dates from gerrit ssh API are wrong until 2013-05 so time to review is only available after that. Time zones are not covered yet. ''

How long is the Gerrit review queue over time? How long does it take to review code contributions? Are we improving? Are Wikimedia's staff and non-staff contributions processed equally? Who is doing better and worse? How to calculate the average time? A few old open changes might distort the picture. What if we compare the pure average of the 100% of commits with the average removing the 10% of slowest and fastest?
 * Number of Wikimedia staff / non-Wikimedia-staff commits reviewed in <2 days, <1 week, <1 month, <3 months, >3 months or unreviewed (values may be fine tuned based on actual data).
 * Same as above, per project. Ranked from slowest to fastest.

One chart with extra data in a table? What kind of chart?

The people and companies and countries analysis will be trivial once we get the size and time to review basic queries working.

Queries
SELECT COUNT(*) FROM issues WHERE status='NEW'; SELECT COUNT(*),YEAR(submitted_on),MONTH(submitted_on) FROM issues WHERE status='NEW' GROUP BY YEAR(submitted_on),MONTH(submitted_on) ORDER BY submitted_on;
 * Size basic for new reviews:
 * Size evolution in time for new reviews:

SELECT count(*) as merged,YEAR(mod_date) AS year, MONTH(mod_date) AS month FROM issues,issues_ext_gerrit WHERE issues.id=issues_ext_gerrit.issue_id AND status='merged' GROUP BY YEAR(mod_date),MONTH(mod_date) ORDER BY mod_date
 * Time evolution for merged reviews

SELECT count(*) as merged,YEAR(mod_date) AS year, MONTH(mod_date) AS month FROM issues,issues_ext_gerrit WHERE issues.id=issues_ext_gerrit.issue_id AND status='abandoned' GROUP BY YEAR(mod_date),MONTH(mod_date) ORDER BY mod_date
 * Time evolution for abandoned reviews

SELECT merged+abandoned+new, t.year, t.month FROM ( SELECT count(*) as merged,YEAR(mod_date) AS year, MONTH(mod_date) AS month FROM issues,issues_ext_gerrit WHERE issues.id=issues_ext_gerrit.issue_id   AND (status='merged' OR status='abandoned' GROUP BY YEAR(mod_date),MONTH(mod_date) ORDER BY mod_date) t, ( SELECT COUNT(*) as new,YEAR(submitted_on) as year,MONTH(submitted_on) as month FROM issues WHERE status='NEW' GROUP BY YEAR(submitted_on),MONTH(submitted_on) ORDER BY submitted_on) t1 WHERE t.year = t1.year and t.month = t1.month; SELECT issues.id, DATEDIFF(max(changed_on),submitted_on) AS revtime, max(changed_on) as date, submitted_by, email FROM issues, changes, issues_ext_gerrit, people WHERE changed_on>'2013-05' AND issues_ext_gerrit.issue_id = issues.id  AND issues.id = changes.issue_id AND issues.submitted_by=people.id  AND field='Code-Review' and new_value='2' GROUP BY changes.issue_id order by revtime desc limit 10 SELECT SUM(revtime)/COUNT(revtime), YEAR(date), MONTH(date) FROM ( SELECT issues.id, DATEDIFF(max(changed_on),submitted_on) AS revtime, max(changed_on) as date, submitted_by, email FROM issues, changes, issues_ext_gerrit, people WHERE changed_on>'2013-05' AND issues_ext_gerrit.issue_id = issues.id    AND issues.id = changes.issue_id AND issues.submitted_by=people.id    AND field='Code-Review' and new_value='2' GROUP BY changes.issue_id order by revtime desc) t GROUP BY YEAR(date),MONTH(date) ORDER BY date;
 * Time evolution for size basic for all reviews SUM (NEW + MERGED month)
 * Time to review basic in days
 * Time to review evolution in time in days

Metrics

 * Total current queue size: 1033
 * Evolution in time queue size (for the current pending reviews), new reviews:

|     NEW |               YEAR |               MONTH |
 * 1 |              2012 |                   3 |
 * 7 |              2012 |                   4 |
 * 11 |              2012 |                   5 |
 * 10 |              2012 |                   6 |
 * 5 |              2012 |                   7 |
 * 11 |              2012 |                   8 |
 * 15 |              2012 |                   9 |
 * 20 |              2012 |                  10 |
 * 21 |              2012 |                  11 |
 * 46 |              2012 |                  12 |
 * 28 |              2013 |                   1 |
 * 59 |              2013 |                   2 |
 * 73 |              2013 |                   3 |
 * 55 |              2013 |                   4 |
 * 145 |              2013 |                   5 |
 * 103 |              2013 |                   6 |
 * 182 |              2013 |                   7 |
 * 241 |              2013 |                   8 |


 * Evolution in time for merged issues

| MERGED | YEAR | MONTH |
 * 15 | 2012 |    2 |
 * 404 | 2012 |    3 |
 * 1399 | 2012 |    4 |
 * 2397 | 2012 |    5 |
 * 2828 | 2012 |    6 |
 * 2468 | 2012 |    7 |
 * 4329 | 2012 |    8 |
 * 2784 | 2012 |    9 |
 * 4283 | 2012 |   10 |
 * 3903 | 2012 |   11 |
 * 4311 | 2012 |   12 |
 * 3752 | 2013 |    1 |
 * 3412 | 2013 |    2 |
 * 3645 | 2013 |    3 |
 * 3216 | 2013 |    4 |
 * 3168 | 2013 |    5 |
 * 3654 | 2013 |    6 |
 * 3958 | 2013 |    7 |
 * 2201 | 2013 |    8 |


 * Evolution in time for abandoned issues

|ABANDONED | YEAR | MONTH |
 * 20 | 2012 |    2 |
 * 101 | 2012 |    3 |
 * 132 | 2012 |    4 |
 * 98 | 2012 |    5 |
 * 171 | 2012 |    6 |
 * 111 | 2012 |    7 |
 * 148 | 2012 |    8 |
 * 136 | 2012 |    9 |
 * 172 | 2012 |   10 |
 * 221 | 2012 |   11 |
 * 162 | 2012 |   12 |
 * 193 | 2013 |    1 |
 * 164 | 2013 |    2 |
 * 337 | 2013 |    3 |
 * 201 | 2013 |    4 |
 * 175 | 2013 |    5 |
 * 207 | 2013 |    6 |
 * 196 | 2013 |    7 |
 * 70 | 2013 |    8 |


 * Evolution in time of queue size for all issues (merged+abandoned+new):

|     TOTAL | YEAR | MONTH |
 * 506 | 2012 |    3 |
 * 1538 | 2012 |    4 |
 * 2506 | 2012 |    5 |
 * 3009 | 2012 |    6 |
 * 2584 | 2012 |    7 |
 * 4488 | 2012 |    8 |
 * 2935 | 2012 |    9 |
 * 4475 | 2012 |   10 |
 * 4145 | 2012 |   11 |
 * 4519 | 2012 |   12 |
 * 3973 | 2013 |    1 |
 * 3635 | 2013 |    2 |
 * 4055 | 2013 |    3 |
 * 3472 | 2013 |    4 |
 * 3488 | 2013 |    5 |
 * 3964 | 2013 |    6 |
 * 4336 | 2013 |    7 |
 * 2512 | 2013 |    8 |


 * Time to review for the Top 10 slowest reviews

|  id  | revtime | date                | submitted_by | email                        |
 * 146 |    437 | 2013-08-16 07:46:28 |           11 | liangent@g           |
 * 208 |    378 | 2013-08-13 03:39:28 |           59 | hashar@f               |
 * 13796 |    317 | 2013-07-22 19:41:39 |          208 | jan@j           |
 * 323 |    307 | 2013-08-02 19:21:13 |           56 | daniel@n   |
 * 17642 |    300 | 2013-08-02 19:17:39 |           90 | chughakshay16@g      |
 * 17641 |    300 | 2013-08-02 19:18:08 |           90 | chughakshay16@g      |
 * 23 |    295 | 2013-08-21 11:12:16 |           30 | amir.aharoni@m |
 * 49272 |    284 | 2013-07-10 23:09:57 |          203 | toniher@c              |
 * 920 |    278 | 2013-07-01 23:09:47 |          105 | helder.wiki@g        |
 * 20147 |    276 | 2013-07-01 17:04:39 |           75 | vitalif@y           |


 * Evolution in time to review in days:

| SUM(revtime)/COUNT(revtime) | YEAR(date) | MONTH(date) |
 * 2.8988 |      2013 |           5 |
 * 2.5753 |      2013 |           6 |
 * 2.7894 |      2013 |           7 |
 * 4.8007 |      2013 |           8 |

Analysis

 * The new reviews size is growing faster in Jul and Aug 2013.
 * The time to review has grown in August
 * Merged issues has declined in August.
 * The rhythm of merged issues changes between months at the start. Now (2013-08) is more stable.
 * High abandoned rate in 2013-03: 337

Issues

 * Time to review is only computed once changes dates are correct: after 2013-05

Code contributors new / gone
Who are the new code contributors (commits + reviews)? Are they increasing their involvement? Who seems to be on a way out or gone? How are our contributor intake & loss evolving? Two charts? Which kind of charts?
 * Number of new contributors with 1 / 2-5 / 6+ changes submitted in the past 3 months (values may be fine tuned based on actual data).
 * (How to register increasing engagement versus one-offs or new contributors disengaging and vanishing after a short period?)
 * Number of contributors stopping contributing or decreasing continuously in the past 3 months.

Related bug report.

Queries

 * New (min(submitted_on)) code contributors for last 3 months with more than 5 contributions:

SELECT id, email, total, age FROM ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,min(submitted_on)) AS age, email  FROM issues, people   WHERE issues.submitted_by=people.id   GROUP BY people.id) a WHERE age <= 90 and total>5 ORDER BY AGE


 * New (min(submitted_on)) code contributors for last 3 months with more than 5 contributions MERGED:

SELECT id, email, total, age FROM ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,min(submitted_on)) AS age, email  FROM issues, people   WHERE issues.submitted_by=people.id AND status='merged'  GROUP BY people.id) a WHERE age <= 90 and total>5 ORDER BY AGE


 * New (min(submitted_on)) code contributors for last 3 months with more than 5 contributions ABANDONED:

SELECT id, email, total, age FROM ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,min(submitted_on)) AS age, email  FROM issues, people   WHERE issues.submitted_by=people.id AND status='abandoned'  GROUP BY people.id) a WHERE age <= 90 and total>5 ORDER BY AGE


 * Gone code contributors, last contributions more than 6 months ago.

SELECT email,age FROM ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,max(submitted_on)) AS age, email  FROM issues, people  WHERE issues.submitted_by=people.id  GROUP BY people.id) t WHERE age > 180 order by age


 * Total gone code contributors, last contributions more than 6 months ago.

SELECT COUNT(email), age FROM ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,max(submitted_on)) AS age, email  FROM issues, people  WHERE issues.submitted_by=people.id  GROUP BY people.id) t WHERE age > 180 order by age


 * Evolution in time of age of gone code contributors:

SELECT COUNT(email) as total, YEAR(last_contrib), MONTH(last_contrib) FROM ( SELECT email, age, last_contrib FROM  ( SELECT people.id, COUNT(*) AS total, DATEDIFF(NOW,max(submitted_on)) AS age, max(submitted_on) AS last_contrib, email FROM issues, people WHERE issues.submitted_by=people.id   GROUP BY people.id) t   WHERE age > 180 order by age ) t1 GROUP BY YEAR(last_contrib), MONTH(last_contrib) ORDER BY last_contrib

Metrics

 * Total new code contributors: 13
 * Total gone code contributors: 127 (total contributors: 394)

| id | email                     | total | age  | 13 rows in set (0.18 sec)
 * New code contributors
 * 21 | bdavis@w     |     6 |    7 |
 * 198 | jack@c |   14 |   31 |
 * 20 | rainerrillke@h |    19 |   40 |
 * 156 | kartik.mistry@g  |    10 |   54 |
 * 332 | karima.rafes@g   |    15 |   58 |
 * 411 | nilesh@n       |    41 |   59 |
 * 409 | simon.eu@g       |     7 |   59 |
 * 360 | abreault@w   |    20 |   65 |
 * 69 | neverett@w   |    46 |   66 |
 * 97 | ebrahim@b      |     9 |   66 |
 * 330 | eu.vlasenko@g    |     6 |   76 |
 * 313 | sam@s      |     7 |   87 |
 * 402 | david@s  |     6 |   88 |


 * New code contributors merged

| id | email                        | total | age  | 10 rows in set (0.17 sec)
 * 21 | bdavis@w        |     6 |    7 |
 * 198 | jack@c   |    12 |   31 |
 * 20 | rainerrillke@h    |    13 |   40 |
 * 411 | nilesh@n          |    31 |   54 |
 * 156 | kartik.mistry@g     |    10 |   54 |
 * 332 | karima.rafes@g      |    14 |   58 |
 * 360 | abreault@w      |    18 |   64 |
 * 69 | neverett@w      |    38 |   66 |
 * 97 | ebrahim@b         |     8 |   66 |
 * 87 | yuvipanda+suchabot@g |   10 |   66 |


 * New code contributors abandoned

| id | email                      | total | age  | 2 rows in set (0.05 sec)
 * 82 | addshore@w    |    15 |   54 |
 * 314 | joel.natividad@o |    6 |   69 |

| total | YEAR(last_contrib) | MONTH(last_contrib) |
 * Evolution of last contribution of gone code contributors:
 * 1 |              2012 |                   2 |
 * 2 |              2012 |                   3 |
 * 7 |              2012 |                   4 |
 * 3 |              2012 |                   5 |
 * 22 |              2012 |                   6 |
 * 13 |              2012 |                   7 |
 * 7 |              2012 |                   8 |
 * 8 |              2012 |                   9 |
 * 11 |              2012 |                  10 |
 * 13 |              2012 |                  11 |
 * 15 |              2012 |                  12 |
 * 8 |              2013 |                   1 |
 * 17 |              2013 |                   2 |

17 people sent their last contribution on 2013-02 and do not contribute more with code submissions.

Analysis

 * 3 new people from WMF, 7 from other email domains

Comments
The analysis could be done also for organization or country, not just people.

Evolution of new comers in time could be really cool.

Bugzilla response time
How long does it take to give a first response to reporters of Low-Immediate / trivial-blocker bugs? How long until acknowledged bugs are resolved? Are we using the importance parameters consistently? Are we improving? Same question as in Gerrit review queue about how to calculate average times.
 * Average time for an accepted bug report between bug creation date and PATCH_TO_REVIEW status being set
 * Average time for an accepted bug report between PATCH_TO_REVIEW status being set and RESOLVED FIXED status being set.
 * Average time for an accepted bug report between bug creation date and first comment by not the reporter her/himself.

Three charts? What chart types?

Related bug report.

Top contributors
Wikimedia professionals apart, who are the top tech community contributors, what are their areas of activity and where are they based? Let's list everybody, not just the top 10. This will help the WMF and the Wikimedia movement knowing and supporting these contributors better. Tables are good. No need for charts?
 * Combined ranking of contributors of Git/Gerrit, Bugzilla, MediaWiki, Mailman, IRC. We'll need to find the formula.
 * Rankings for each channel.

Related bug report.

Team
Quim Gil from the Wikimedia Engineering Community team is coordinating the Metrics Dasboard project, which is being implemented by Bitergia as contractors.

The Bitergia team working in the MediaWiki dashboard is formed by Daniel Izquierdo, Luis Cañas and Jesus Gonzalez Barahona and Alvaro del Castillo as project manager.

The ownership of this project will transition to the Wikimedia Analytics team during 2013-14.