13 Apr
2015
13 Apr
'15
2:30 p.m.
Hello Alex,
The preprocessing step could have been done with Moose/Pharo, as it
basically includes a log parser and a model to handle removed/added APIs.
The main problem I faced was to host such a big database generated after
the preprocessing step.
So, I decided to use google app engine (then I should use some of their
supported languages - python in my case).
bets regards,
On Fri, Apr 10, 2015 at 2:22 PM, Alexandre Bergel <alexandre.bergel(a)me.com>
wrote:
hi!
Would be great to hear what is missing in Moose to conduct such a study in
it?
Alexandre
--
_,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:
Alexandre Bergel http://www.bergel.eu
^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;.
On Apr 10, 2015, at 9:58 AM, Andre Hora <andrehoraa(a)gmail.com> wrote:
Hello guys,
I would like to present you apiwave <http://apiwave.com/>, a tool to
discover and track APIs.
While it is easy to know how “popular” is a project in number of
contributors or fans, it’s quite hard to know how many clients are actually
using it.
To cover that, we performed an analysis on the most used APIs in top 500
GitHub java projects. On apiwave <http://apiwave.com/> you can dig into
this data, and explore how more than 250K frameworks/packages/APIs are
actually being used over time. You can read a bit more in this post
<https://apiwave.wordpress.com/2015/04/10/most-used-apis-in-top-500-github-java-projects/>
.
Even if the tool is not directly related with Moose, I think it could be
interesting for some developers here :)
Feel free to provide feedback.
best regards,
--
Andre Hora
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--
Andre Hora