[openstack-dev] Grizzly's out - let the numbers begin...

Daniel Izquierdo dizquierdo at bitergia.com
Mon Apr 8 14:16:05 UTC 2013

Hi again,

On 04/05/2013 09:18 PM, Daniel Izquierdo wrote:
> Hi Eric,
> On 04/05/2013 08:31 PM, Eric Windisch wrote:
>> On Friday, April 5, 2013 at 14:17 PM, Stefano Maffulli wrote:
>>> Let me pull in the authors of the study, as they may be able to shed
>>> some light on the inconsistencies you found.
>>> Eric, Joshua: can you please send Daniel and Jesus more details so they
>>> can look into them?
>> I made a note on the blog. The response to others indicates that 
>> their results are based on two different methodologies (git-dm and 
>> their own dataset analysis), this would likely be the source of 
>> differences in numbers.  I haven't noticed variations anywhere except 
>> author counts, but I haven't looked very hard, either.
Charts are now updated [1]. The bug as mentioned was found in the 
queries, where we were counting people not taking into account unique 
identities (in some cases a developer may use more than one identity to 
commit changes to the source code).

Thus charts and tables are now updated (and should contain consistent 
data). You will notice a small increase of commits in Rackspace and 
small decrease in Canonical. Those are due to a developer that was 
initially wrongly assigned to Canonical for the whole history.

Again, our idea is to help you in the better understanding of how 
OpenStack is being developed and main actors involved in it, so any 
feedback is more than welcome. Indeed, our intention for the following 
steps is to provide closer information to developers, so this could be 
useful in the software development process. We have our own ideas, but 
you could probably have better ones.

Thanks a lot for your comments and see you in Portland!

[1] http://bitergia.com/public/reports/openstack/2013_04_grizzly/

> The methodology we have used to match developers and affiliations is 
> based on information partially obtained from the OpenStack gitdm 
> project, but also compared to our own dataset (that we already had 
> from previous releases). Sorry if I didn't explain myself consistently 
> in the blog.
> The bug here is related to how we're calculating data for the 
> spreadsheets and company by company. The result is that the company by 
> company analysis had a bug, and we were counting some more developers 
> than expected and commits (we were counting for instance as two 
> different people a developer who used at some point two different 
> email addresses).
> So, the data at the tables (bottom part in the main page) is the 
> correct one. The data for the source code management system in the 
> left part of each of the companies is overestimated.
> In addition, the number of commits in Rackspace will be a bit higher 
> for the next round. Another developer told us that he moved from one 
> company to Rackspace at some point, so you will see how that number 
> will increased a bit.
>> I guess it could also be differences or errors in employee->company 
>> mappings? Perhaps instead, one methodology includes those that report 
>> bugs, while the other only accounts for git? I'm not sure.
> Regarding to this point, the data about bug tracking system and 
> mailing lists is only based on activity from developers. This means 
> that people that have not committed a change to the source code are 
> not counted as part of the activity of companies in Launchpad and 
> Mailing Lists. In any case and as an example, we're covering around a 
> 60% of the activity in the mailing lists because people that at some 
> point submitted changes to the Git are that active.
> Our purpose with this is to show only activity from developers and 
> their affiliations through the three data sources (git, tickets and 
> mailing lists). This is also an option. From our point of view this 
> analysis was pretty interesting, but perhaps for others this is not 
> good enough.
>> Other things like dividing commits/authors seems to just be the wrong 
>> methodology where a median would be more appropriate and harder to game.
> This is a good point. As you mention it is probably more fair to have 
> such metric. At some point we would like to show some boxplots and 
> other metrics to better understand the distribution of the datasets, 
> but we had to choose some. In any case, we will take into account this 
> for the next reports for sure. Thanks!
> Probably a good approach would be to have a common view with all of 
> the people interested in this type of analysis. In this way we could 
> reach an agreement about how to visualize data, necessary and 
> interesting metrics, common methodology to measure stuff and projects 
> involved. This analysis is just a possibility, but there are some more 
> for sure.
> In any case, please, let us know any other concerns you may have and 
> any feedback of the community is more than appreciated.
> Thanks a lot for all your comments.
> Regards,
> Daniel Izquierdo.
>> Regards,
>> Eric Windisch

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