Re: Driver model.. expel legacy drivers?

[John Richard Moser <nigelenki@comcast.net>]

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Horst H. von Brand wrote:
> John Richard Moser <nigelenki@comcast.net> wrote:
> 
> [...]
> 
>> I've mapped the growth of the .tar.bz2 archives in kilobytes since
>> 2.6.0, they show an erratic pattern but a strong overall linear growth
>> pattern.  This means the actual size of the kernel is polynomial and
>> integrates crudely to:
>>
>>    18.59x^2+133.1x+32600
>>
>> For x == minor (i.e. 2.6.0 == 0; 2.6.18 == 18).  This produces a level
>> of error; however, I've graphed the error and it seems to be off by no
>> more than 400k ever and show a horizontal trend (i.e. overall accurate);
>> however I'll have to apply the same prediction to future kernel versions
>> to get a good picture.
> 
> Hum... perhaps going against time (not minor) is better?
> 

I think revisions have an average time between them that follows a
general linear trend.  {1 4 3 1 0 2 2 3} is a general linear trend; a
line between these points best dividing half above and half below is
horizontal.  *The assertion that revision numbers are linearly
correlated to time is a conjecture; I have not verified this
mathematically.*

> You could also include the whole 2.5.x set (at least since git became
> common) for a larger series...

Perhaps, but that was a heavy development period and I want to avoid
lurking variables; otherwise I'd have included 2.4's whole series too.
I know this is a lost cause in 2.6, what with things like devfs or OSS
dropping and ALSR getting merged in at random times....

> 
> [...]
> 
>> My math predicts that 2.6.57 (+39) will be 100M (in approximately 7
>> years if you assume 1 kernel release every 2 months); 2.6.92 (+35) will
>> breech 200M; 2.6.117 (+25) will breech 300M; and 2.6.138 (+21)) will
>> breech 400M.  That should suffice for predictions over the next 20 years
>> based on this crude model.
> 
> I'd trust your curve for, say, 5 minors. Not more. The quadratic term is
> rather hard to justify in any case... linear growth (== new drivers at a
> (roughly) constant rate, a (roughly) constant number of people actively
> working on the kernel with constant productivity, ...) I give you easily.

(ax^2 + bx + c)d/dx == 2ax + b

I didn't eye the curve as quadratic; I eyed it as a gentle curve.  I
took the differences and looked for a trend specifically because I know
a linear growth trend (polynomial degree 1) indicates a quadratic trend
(polynomial degree 2).

As I said, I don't have enough samples.  I only used 16 of the 19
samples I have to generate the function above; I would like upwards of
30 before claiming any useful trend.

- --
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