Why is ValueType.GetHashCode() implemented like it is?
The actual implementation of ValueType.GetHashCode() doesn't quite match the comment. It has two versions of the algorithm, fast and slow. It first checks if the struct contains any members of a reference type and if there is any padding between the fields. Padding is empty space in a structure value, created when the JIT compiler aligns the fields. There's padding in a struct that contains bool and int (3 bytes) but no padding when it contains int and int, they fit snugly together.
Without a reference and without padding, it can do the fast version since every bit in the structure value is a bit that belongs to a field value. It simply xors 4 bytes at a time. You'll get a 'good' hash code that considers all the members. Many simple structure types in the .NET framework behave this way, like Point and Size.
Failing that test, it does the slow version, the moral equivalent of reflection. That's what you get, your KeyValuePair<> contains references. And this one only checks the first candidate field, like the comment says. This is surely a perf optimization, avoiding burning too much time.
Yes, nasty detail and not that widely known. It is usually discovered when somebody notices that their collection code sucks mud.
One more excruciating detail: the fast version has a bug that bytes when the structure contains a field of a type decimal. The values 12m and 12.0m are logically equal but they don't have the same bit pattern. GetHashCode() will say that they are not equal. Ouch.
UPDATE: This answer was (in part) the basis of a blog article I wrote which goes into more details about the design characteristics of GetHashcode. Thanks for the interesting question!
I didn't implement it and I haven't talked to the people who did. But I can point out a few things.
(Before I go on, note that here I am specifically talking about hash codes for the purposes of balancing hash tables where the contents of the table are chosen by non-hostile users. The problems of hash codes for digital signing, redundancy checking, or ensuring good performance of a hash table when some of the users are mounting denial-of-service attacks against the table provider are beyond the scope of this discussion.)
First, as Jon correctly notes, the given algorithm does implement the required contract of GetHashCode. It might be sub-optimal for your purposes, but it is legal. All that is required is that things that compare equal have equal hash codes.
So what are the "nice to haves" in addition to that contract? A good hash code implementation should be:
1) Fast. Very fast! Remember, the whole point of the hash code in the first place is to rapidly find a relatively empty slot in a hash table. If the O(1) computation of the hash code is in practice slower than the O(n) time taken to do the lookup naively then the hash code solution is a net loss.
2) Well distributed across the space of 32 bit integers for the given distribution of inputs. The worse the distribution across the ints, the more like a naive linear lookup the hash table is going to be.
So, how would you make a hash algorithm for arbitrary value types given those two conflicting goals? Any time you spend on a complex hash algorithm that guarantees good distribution is time poorly spent.
A common suggestion is "hash all of the fields and then XOR together the resulting hash codes". But that is begging the question; XORing two 32 bit ints only gives good distribution when the inputs themselves are extremely well-distributed and not related to each other, and that is an unlikely scenario:
// (Updated example based on good comment!)
struct Control
{
string name;
int x;
int y;
}
What is the likelihood that x and y are well-distributed over the entire range of 32 bit integers? Very low. Odds are much better that they are both small and close to each other, in which case xoring their hash codes together makes things worse, not better. xoring together integers that are close to each other zeros out most of the bits.
Furthermore, this is O(n) in the number of fields! A value type with a lot of small fields would take a comparatively long time to compute the hash code.
Basically the situation we're in here is that the user didn't provide a hash code implementation themselves; either they don't care, or they don't expect this type to ever be used as a key in a hash table. Given that you have no semantic information whatsoever about the type, what's the best thing to do? The best thing to do is whatever is fast and gives good results most of the time.
Most of the time, two struct instances that differ will differ in most of their fields, not just one of their fields, so just picking one of them and hoping that it's the one that differs seems reasonable.
Most of the time, two struct instances that differ will have some redundancy in their fields, so combining the hash values of many fields together is likely to decrease, not increase, the entropy in the hash value, even as it consumes the time that the hash algorithm is designed to save.
Compare this with the design of anonymous types in C#. With anonymous types we do know that it is highly likely that the type is being used as a key to a table. We do know that it is highly likely that there will be redundancy across instances of anonymous types (because they are results of a cartesian product or other join). And therefore we do combine the hash codes of all of the fields into one hash code. If that gives you bad performance due to the excess number of hash codes being computed, you are free to use a custom nominal type rather than the anonymous type.