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Firefox version trends

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A few months ago (middle of 2011) I was bewildered to find out that Mozilla decided to retire Firefox 4 from security support after only a couple of months from the release date, crapping on huge companies in the process.

Anyway, I stayed on Firefox 3.6, which continued to be the latest stable in Gentoo, until several days ago when it suddenly jumped to 5 6 7. Wait, what???

So I checked and found out that the Firefox people started spinning numbers like crazy, and they actually plan to release version 10 by the end of Jan 2012. It looks like a nuclear reactor explosion with massive releases of radiation, except.. apparently it's all intentional. Failing to make any sense of it, I decided to just study the process.

The other part of the story is that I've been studying some free online courses organized by in partnership with Stanford University. In the machine learning course I learned (so far) about linear regression and various related techniques, as well as a programming language called Octave, which is very suitable for numerical computations.

So I went ahead to plot the release dates of major Firefox versions (taken from Wikipedia), and do a polynomial regression to estimate the trend. I had a bunch of hurdles but I managed to overcome them, with the help of the friendly people from #octave on freenode. Here is the result:

Firefox version graph

The dates for versions 8, 9 and 10 are expected release dates. I found the best fit with a polynomial of degree 5; not perfect, but pretty close. According to the estimation, we will be getting close to Firefox 30 by the end of 2012. Unless Mozilla decides to just do away with version numbers, or destroy the project completely. As for me, I'm still sticking with my primary browser - SeaMonkey.

Created on 04 Nov 2011, last updated on 04 Nov 2011 Valid HTML5

Comments:

Erik's avatar
Erik

Woah. Just woah.

19 Apr 2017

From 2009 up to middle 2010 you can see FF versions going DOWN. WTF?

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aditsu's avatar
aditsu

Re: Woah. Just woah.

19 Apr 2017

Linear/polynomial regression is not perfect :) Especially when used so straightforwardly. It can't easily deal with the sudden spike that happened in 2011. There may be better techniques to approximate/estimate the data points, but I thought this was an interesting exercise.

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