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