> On 12 Jan 2016, at 20:59, stepharo <[email protected]> wrote:
> 
> Hi david
> 
> I rad the wikipedia page you mention and this looks a bit obvious to me. I 
> knew this.
> now it does not really help fixing the problem you mention.
> 
> Stef

Since you asked for it…

The #hash method is used in Pharo to separate objects in bucket-based data 
structures.

It must have one required property which is required data integrity:

A. Objects that are equal according to #= must have equal hashes.

It should have two desirable properties that are required to support the 
algorithmic assumptions of bucket-based data structures:

B. Objects that are not equal should have different hashes. Ideally, the 
probability of hash collision should by 1/N where N is the size of hash value 
space.
C. The hash values should spread as much as possible over their value space. 
For example: ProtoObject>>#identityHash.

How these two desirable properties can be implemented depend on the actual 
distribution of the value used to compute the hash.

An object can safely use XOR hashing if its instance variables are all 
different objects that already provide a hash method with these two properties. 
For example, an object whose behaviour is defined by several of singleton 
delegates of different classes that do not override Object>>#hash.

But if the instance variables are not guaranteed to have those properties, it 
is necessary to more thoroughly "mix the bits". For example: 
SequenceableCollection>>#hash.

hash
        | hash |

        hash := self species hash.
        1 to: self size do: [:i | hash := (hash + (self at: i) hash) 
hashMultiply].
        ^hash

The mixing of the bits is done by the combination of addition and hashMultiply. 
The value of "species hash" does not need to be processed by hashMultiply, 
because it is probably computed by ProtoObject>>identityHash, and that already 
provides C.

LayoutFrame is a particularly good example of a data structure that should not 
use XOR hashing. Its instance variables provide none of the required 
properties: SmallInteger>>#hash is just ^self. In addition, common LayoutFrame 
instances tend to use pairs of identical values in their instance variables. 
Like 0@0 corner: 1@1, or Margin fromNumber: 10.

A good hash function for LayoutFrame needs to:

Get hashes for each instance variable that provides A and B.
Combine them in a way that is order-sensitive (to maintain B) and that does 
some extra mixing (to provide C).

Now, we can assume that common values for the instance variables will be 
instances of SmallInteger, Float, or Fraction.

By the way, you can see in Fraction>>#hash, that a comment mentions the 
assumption that the fraction is already reduced, that is what makes it 
acceptable to use bitXor.

The hash of SmallInteger does provide A and B, but not C. The hash of Float is 
harder to understand, but tests show that it provide distinct values for 0.5, 
0.25 and 0.125. So it hopefully provides B for the range of values of interest 
to LayoutFrame.

Another class that has similar hashing constraints to LayoutFrame is Point. Its 
hash method is:

hash
        "Hash is reimplemented because = is implemented."

        ^(x hash hashMultiply + y hash) hashMultiply

It does not include species in the computation, which is less than ideal 
because it favours collisions with objects of different species that have a 
similar content and a the same #hash algorithm.

Finally, it is probably not necessary or useful to use the accessors to get to 
the instance variables.

So a good implementation would be this (untested, there might be a typo or two)

hash
        | hash |
        hash := self species hash
        hash := (hash + leftFraction hash) hashMultiply
        hash := (hash + leftOffset hash) hashMultiply
        hash := (hash + topFraction hash) hashMultiply
        hash := (hash + topOffset hash) hashMultiply
        hash := (hash + rightFraction hash) hashMultiply
        hash := (hash + rightOffset hash) hashMultiply
        hash := (hash + bottomFraction hash) hashMultiply
        hash := (hash + bottomOffset hash) hashMultiply
        ^ hash

I am sure you could have figured that by yourself, by thinking about how hash 
values are used and by looking at the code of kernel classes, instead of 
getting offended and turning all defensive.

I hope we can both learn from this episode. I do not enjoy antagonising people, 
but I will not write lengthy messages like this one every time someone 
questions my thinking.

Have a nice day.

> Le 11/1/16 10:09, David Allouche a écrit :
>> Since it's not obvious why xor-ing is a bad way to produce hash, here is a 
>> link that gives some background
>> 
>> https://en.wikipedia.org/wiki/Hash_function#Uniformity
>> 
>>> On 11 Jan 2016, at 10:01, David Allouche <[email protected]> wrote:
>>> 
>>> I happened to look at the new code for LayoutFrame>>#hash
>>> 
>>> hash
>>>     ^self species hash bitXor:
>>>             (self leftFraction bitXor:
>>>             (self leftOffset bitXor:
>>>             (self topFraction bitXor:
>>>             (self topOffset bitXor:
>>>             (self rightFraction bitXor:
>>>             (self rightOffset bitXor:
>>>             (self bottomFraction bitXor:
>>>             self bottomOffset)))))))
>>> 
>>> This is a terrible, terrible way to compute a hash.
>>> 
>>> 0 xor 0 = 1 xor 1 = 2 xor 2 = etc.
>>> 
>>> NEVER compute hashes with xor, that's wrong, and it causes horrible, hard 
>>> to debug, performance bugs down the road.
>>> 
>>> SequenceableCollection>>#hash looks more like a correct way of doing it. I 
>>> do not know what is the correct, efficient way to reuse this logic in 
>>> LayoutFrame>>#hash.
>>> 
>>> By the way, how do you guys do code reviews for code integrated into the 
>>> core?
>>> 
>> 
>> 
> 
> 

Reply via email to