On Mon, 30 Jan 2006, Prof Brian Ripley wrote:
> On Mon, 30 Jan 2006 [EMAIL PROTECTED] wrote:
>
>> On 1/30/2006 1:39 PM, Ionut Florescu wrote:
>>> Thank you for the quick reply, I will look into the R packages.
>>> For crashing R try this:
>>>
>>> generator.zp=function(x,p)
>>> {a=1:(p-1); b=x^a%%p;
>>> if(all(b[1:(p-2)]!=1)&&(b[p-1]==1)){return(x, " Good ")}
>>> else{return(x, " No Good, try another integer ")}
>>> }
>>
>> Thanks, I can reproduce the crash using
>>
>> for (x in 10:100) generator.zp(x, 41)
>>
>> I'll see if I can track down what's going wrong. By the way, you're not
>> supposed to use two arguments to return(): that's not supposed to be
>> allowed any more. I'm somewhat surprised you don't get an error from
>> it. But that's not the cause of the crash.
>
> You do get a warning, though. It *is* allowed, see ?return.
>
> One error is the following in real_binary:
>
> if (n1 > n2)
> copyMostAttrib(s1, ans);
> else if (n1 == n2) {
> copyMostAttrib(s2, ans);
> copyMostAttrib(s1, ans);
> }
> else
> copyMostAttrib(s2, ans);
>
> Here ans is not PROTECTED.
I think this one was a consequence of the other one. I did get a valgrind
error from there, but it looks as if copyMostAttrib does the necessary
protection, if ans has not already been damaged.
> The second is in the warning, which causes allocation when ans is not
> protected.
>
> Fixed in R-devel and 2.2.1 patched.
>
>
>> Duncan Murdoch
>>
>>
>>>
>>> This checks if element x is a generator of the group Z_p. If you try
>>> this function for p = 41 and x various increasing values eventually it
>>> will crash R. That is what I meant by random, at first I started x=2,3
>>> so on, when I got to 8, R crashed. Now apparently I can get to 15. When
>>> I tried again I got to 20.
>>>
>>> Ionut Florescu
>>>
>>>
>>> Duncan Murdoch wrote:
>>>> On 1/30/2006 11:32 AM, Ionut Florescu wrote:
>>>>> I am a statistician and I come up to an interesting problem in
>>>>> cryptography. I would like to use R since there are some statistical
>>>>> procedures that I need to use.
>>>>> However, I run into a problem when using the modulus operator %%.
>>>>>
>>>>> I am using R 2.2.1 and when I calculate modulus for large numbers
>>>>> (that I need with my problem) R gives me warnings. For instance if
>>>>> one does:
>>>>> a=1:40;
>>>>> 8^a %% 41
>>>>> one obtains zeros which is not possible since 8 to any power is not a
>>>>> multiple of 41.
>>>>> In addition when working with numbers larger that this and with the
>>>>> mod operator R crashes randomly.
>>>>
>>>> Could you keep a record of the random crashes, and see if you can make
>>>> any of them repeatable? R shouldn't crash. If you can find a
>>>> repeatable way to make it crash, then that's a bug that needs to be
>>>> fixed. (If it crashes at random it should still be fixed, but it's so
>>>> much harder to fix that it's unlikely to happen unless the cases are
>>>> ones that look likely to come up in normal situations.)
>>>>
>>>>
>>>>>
>>>>> I believe this is because R stores large integers as real numbers
>>>>> thus there may be lack of accuracy when applying the modulus operator
>>>>> and converting back to integers.
>>>>>
>>>>> So my question is this: Is it possible to increase the size of memory
>>>>> used for storing integers? Say from 32 bits to 512 bits (Typical size
>>>>> of integers in cryptography).
>>>>
>>>> No, but there is at least one contributed package that does multiple
>>>> precision integer arithmetic. I can't remember the name of it right
>>>> now, but Google should be able to find it for you...
>>>>
>>>> Duncan Murdoch
>>>>>
>>>>> Thank you, any help would be greatly appreciated.
>>>>> Ionut Florescu
>>>>>
>>>>> ______________________________________________
>>>>> R-help@stat.math.ethz.ch mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide!
>>>>> http://www.R-project.org/posting-guide.html
>>>>
>>>>
>>
>> ______________________________________________
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>>
>>
>
> --
> Brian D. Ripley, [EMAIL PROTECTED]
> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272866 (PA)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
>
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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