[aadl]: Question about error model events distribution

[Viet Yen Nguyen]

Hi Denis,

1) Regarding time periods: the time period is implicit to the \lambda
parameter. You of course have to make sure that all \lambda parameters in
the model are based on the same time period. See also the definition of the
Poisson distribution on Wikipedia.

2) Regarding the syntax and use of the distributions, I don't have a copy
of the AADL Error Annex here at hand (the copy I used to have belonged to
the my previous employer). I cannot therefore lookup and confirm for you
whether the current text is formal enough on this. Perhaps somebody on the
mailinglist who is more intimate with the AADL Error Annex can jump in
here.

3) Theoretically, any probability distribution is oblivious towards its
use. Its semantics are decoupled from the meaning of the random variable
that is being probabilistically distributed. So far we've been taking about
amount of occurrences, waiting times and decision answers as random
variables. The choice of distribution for a random variable therefore
depends on whether the distribution's characteristics match your intended
semantics (i.e. the real world).

Viet Yen

On Wed, Oct 22, 2014 at 2:03 PM, Denis Buzdalov <buzdalov at ispras.ru> wrote:

> Hi Viet Yen,
>
> Thank you for your response. But, you know, I still have questions to
> your answer.
>
> > Let us translate that to practical terms. The sample 1 means that the
> > error event occurs 1 time (within the timeframe according to the
> > \lambda parameter of the Poisson distribution). The sample 100 means
> > that the error event occurs 100 times.
>
> The first question is what period of time event occurrence is
> considered? This distribution shows the probability of n occurrences of
> event during what period of time?
>
> > Given the \lambda parameter,
> > the Poisson distribution assigns a probability to that, e.g. the
> > probability that the error event occurs 100 times.
>
> The second question is am I right that you mean that \lambda parameter
> can be set through the 'ProbabilityValue' record part of the
> 'EMV2::OccurrenceDistribution' property value?
>
> If the answer is 'yes', then another question rises: how would you
> set parameters for multiple-parameterized distributions (like the Normal
> distribution)?
>
> If the answer to the second question is 'no' then I would ask how would
> you set the \lambda parameter?
>
> > Another interesting distribution is the exponential one. It's
> > continuous and spawns a probability distribution over the waiting
> > time before the error event happened. For example, the probability
> > that you're 100 time units in the OK state before the error event
> > happens.
>
> This part of your answer makes me messed up completely.
>
> Am I right that you mean that the semantics of distribution setting
> depends completely on the distribution type: you have
> - the probability of occurrence in one case,
> - expected count of occurrences in the other case and
> - expected time on the third case?
>
> Are you sure that it is formalized enough (e.g. in the standard text)
> to be used by instruments or formal analysis?
>
> --
> Denis Buzdalov
> Software Engineering Department, ISPRAS
>
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