Develop Reference

Create a identical "random" float based on multiple data

I'm working on a game (Unity) and I need to create a random float value (between 0 and 1) based on multiple int and/or float.
I think it'll be more easy to manually create a single string for the function, but maybe it could accept a list of int and/or float.
Example of result:
"[5-91]-52-1" > 0.158756..
Important points:
The distribution of results (between 0 and 1) must be equals (don't want 90% of results between 0.45 and 0.55)
Asking 2 times for the same string must return the exact same result (even if I reload the app, or start it on different computers, ..)
Results have no need to be unique.
Bonus Point:
Sometime I need that close similar string return close result, but not everytime. It's possible for "random generation" to handle a boolean with this feature ?

What you've described is essentially definition of a hash function.
So just use one and normalize results into range you want. Most basic case can use GetHashCode, but it is not guaranteed to produce the same results across different versions of framework.
Stable version that guarantees to provide exactly the same results across machines would be to use well known good hash - like crypto hash SHA256 and take several first bytes of result as integer and normalize. Crypto hash functions also conveniently take byte arrays as input so you can combine multiple values as bytes directly and get stable result.
var intValue = 42;
var bytesToHash = BitConverter.GetBytes(intValue);
var hash = System.Security.Cryptography.SHA256Managed.Create()
.ComputeHash(bytesToHash);
var toNormalize = BitConverter.ToUInt32(hash,0);
var fancyRandom = (double)toNormalize/UInt32.MaxValue;
To combine multiple values into byte array you can either manually combine results of BitConverter.GetBytes or use BinaryWriter on MemoryStream.
Alternatively you can use resulting integer as seed for some custom implementation of pseudo-random generator (as one in .Net does not guarantee to provide same results across machines/version of .Net) as suggested in comments, but I don't think it will give significantly better distribution.
Note: make sure resulting numbers are distributed "randomly enough" for your case. Crypto hashing functions likely give result you want but I'm not sure how to prove that.
For "bonus" part: I would be very surprised if you can find pseudo-random generator that will consistently produce close results for "similar" seeds. Instead you can use same approach as above for separate parts - one that "same" and other that handles variation (i.e. intValue & 0xFFFFFF00 for stable part, intValue & 0xFF for "small difference") and than combine resulting "random" numbers with some weight: randomFromStable + 0.05 * randomFromDifference.

I would suggest using the hashcode (or something similar) as the seed to a Random object. Hashcodes must be the same for the same string so you will always get the same sequence back.
As Nuf notes, hashcodes are only guaranteed to be the same in the same app-domain; so it may not work across restarts.
As to your bonus point, getting there without writing your own RNG will be hard. Any variance in the seed can and should cause a lot of variation in the resulting sequence.

Does a perfect hash function guarantee no collisions?

I have been reading and learning hashing and hashtables and experemented with some code(I am still very new to this so I might say something wrong that I missunderstood). I came to the issue for perfect hash functions. Provided that I have my own custom type that somehow has a perfect hash function:
class Foo
{
private int data;
override int GetHashCode()
{
return data.GetHashCode();
}
}
An int's hash code is the int itself so I have a perfect hash function, right? But when we use the hashing function to map the objects to a hashtable by the simple formula:
index = foo.GetHashCode() % hashtable.Length
we get a variable index that depends on also how many elements we have in the hashtable. If the hashtable's size was int.MaxValue only then we will have a perfect hash function. For example lets say that we have a hashtable with size of 2. And if we hash for example the numbers 1 and 3 we get
1 % 2 = 1
3 % 2 = 1
A collision! Have I understood anything wrong about hashing and hashtables? It comes out that a perfect hash function is not perfect.

You have it all right until this point
index = foo.GetHashCode() % hashtable.Length
Your hash function is perfect, but when you calculate the modulo, you're actually using a different hash function. In this case, your hash function int.GetHashCode is perfect, but your data structure using foo.GetHashCode() % hashtable.Length is not. That is, one thing is the hash of your objects, and a different thing is the hash used by the structure holding those objects.
For your data structure to be perfect too, its maximum size must also be the number of ints.
So why don't we have collisions in Dictionary? Actually, we do. If two objects A and B do have the same hash in the dictionary, we have a collision. What happens is that the dictionary runs A.Equals(B) as the final check to see if the two objects actually are the same or not. If they are, you get an exception for having duplicates. If they don't, they are both kept under the same dictionary hash.

Yes! (as said, by definition)
Where do you get a p.h.f from in the first place?
You want to hash a fixed, i.e. constant set S of different (i.e. no multiset) values
to the set 1..|S|, bijectively.
Apparently then, the p.h.f depends on the set S.
Also, remove a single element from S, and add another one, you almost surely get a collision (of the new element with an old one).
So, you actually want "a p.h.f. for such-and-such well defined/described set".
And then we can try to find one.

Yes, a perfect hash function is guaranteed not to have collisions.
That's its very definition!
From Wikipedia (http://en.wikipedia.org/wiki/Perfect_hash_function)
A perfect hash function for a set S is a hash function that maps distinct elements in S to a set of integers, with no collisions. A perfect hash function has many of the same applications as other hash functions, but with the advantage that no collision resolution has to be implemented

Hashes (MD5, SHA1, SHA256, SHA384, SHA512) - why isn't it possible to get the value back from the hash?

On this blog post, there is a sentence as below:
This hash is unique for the given text. If you use the hash function
on the same text again, you'll get the same hash. But there is no way
to get the given text from the hash.
Forgive my ignorance on math but I cannot understand why it is not possible to get the given text from the hash.
I would understand if we use one key to encrypt the value and another to decrypt but I cannot figure it out in my mind. What is really going on here behind the scenes?
Anything that clears my mind will be appreciated.

Hashing is not encryption.
A hash produces a "digest" - a summary of the input. Whatever the input size, the hash size is always the same (see how MD5 returns the same size result for any input size).
With a hash, you can get the same hash from several different inputs (hash collisions) - how would you reverse this? Which is the correct input?
I suggest reading this blog post from Troy Hunt on the matter in order to gain better understanding of hashes, passwords and security.
Encryption is a different thing - you would get a different cypher from the input and key - and the size of the cypher will tend to be larger as the input is larger. This is reversible if you have the right key.
Update (following the different comments):
Though collisions can happen, when using a cryptographically significant hash (like the ones you have posted about), they will be rare and difficult to produce.
When hashing passwords, always use a salt - this reduces the chances of the hash being reversed by rainbow tables to almost nothing (assuming a good salt has been used).
You need to decide about the tradeoffs of the cost of hashing (can be processor intensive) and the cost of what you are protecting.
As you are simply protecting the login details, using the .NET membership provider should provide enough security.

Hash functions are many to one functions. This means that many inputs will give the same result but that for any given input you get one and only one result.
Why this is so can be intuitively seen by considering a hash function that takes a string input of any length and generates a 32 bit integer. There are obviously far more strings than 2^32 which means that your hash function cannot give each input string a unique output. (see http://en.wikipedia.org/wiki/Pigeonhole_principle for more discussion - the Uses and applications section specifically talks about hashes)
Given we now know that any result from our hash function could have been generated from one or more inputs and we have no information other than the result we have no way to determine which input was used so it cannot be reversed.

There are at least two reasons:
Hashing usually uses asymmetric functions for calculations - meaning that finding reverse value of some operation is MUCH more difficult (in time/resources/efforts) than the direct operation.
Hashes of same algorithm are always of the same length - meaning there is a limited set of possible hashes. This means that for every hash there will be infinite number of collisions - different source data block which form the same hash value.

It's not encrypt/decrypt. For example, simple hash function:
int hash(int data)
{
return data % 2;
}
Problem?

Hashing is like using a checksum to verify data, not to encrypt or compress data.

This is essentially math, a Hash function is a function that is NOT 1 to 1. It takes a Range of inputs in the set of all binary data B* and maps it to some fixed length binary string set Bn for fixed n or so.( this definition is onto however)
you can try and calculate the pre-image, of a given hash via brute force, but without knowing the size, it is infinite.

You can hash any length of data you want, from a single byte to a terabyte file. All possible data can be hashed to a 256 bit value (taking SHA-256 as an example). That means that there are 2^256 possible values output from the SHA-256 hash algorithm. However, there are a lot more than 2^256 possible values that can be input to SHA-256. You can input any combination of bytes for any length you want.
Because there are far more possible inputs than possible outputs, then some of the inputs must generate the same output. Since you don't know which of the many possible inputs generated the output, it is not possible to reliably go backwards.

A very simple hash algorithm would be to take the first character of each word within a text. If you take the same text you can always get out the same hash but it is impossible to rebuilt the original text from only having the first character of each word.
Example hash from my answer above:
AvshawbtttfcoewwatIyttstycagotshbisitrtotfohtfcoew
And now try to find out the corresponding text from the given hash. ;-)

Decrypt hash string from String.GetHashCode?

From this sample code from MSDN
http://msdn.microsoft.com/en-us/library/system.string.gethashcode.aspx
The hash code for "abc" is: 536991770
But how to convert back the "536991770" to "abc"?

The is no way to get value from the hashcode. See hash-function definition.
Hash values are not used to uniquely identify the original value, have values are not unique for each type of the input value.
A hash function may map two or more
keys to the same hash value. In many
applications, it is desirable to
minimize the occurrence of such
collisions, which means that the hash
function must map the keys to the hash
values as evenly as possible.

You cannot. Hashes are one way.
The thing with hashes is that you loose information. Independent of the length of the string, the result is always an integer. This means e.g. that getting the has of a string of 10,000 characters will also result in an integer. It is of course impossible to get the original string back from this integer.

There is no way to "decrypt" the hash code. Amongst other reasons, because two different strings may very well produce the same hash code. That feature alone would make it impossible to reverse the process.

You cannot,
Even if you will have a table with all strings in the world and their hash code you wouldn't be able to achieve that since there are more string then ints (~4 billion ints) so there are several strings that result in the same hash code.

What hash algorithm does .net utilise? What about java?

Regarding the HashTable (and subsequent derivatives of such) does anyone know what hashing algorithm .net and Java utilise?
Are List and Dictionary both direct descandents of Hashtable?

The hash function is not built into the hash table; the hash table invokes a method on the key object to compute the hash. So, the hash function varies depending on the type of key object.
In Java, a List is not a hash table (that is, it doesn't extend the Map interface). One could implement a List with a hash table internally (a sparse list, where the list index is the key into the hash table), but such an implementation is not part of the standard Java library.

I know nothing about .NET but I'll attempt to speak for Java.
In Java, the hash code is ultimately a combination of the code returned by a given object's hashCode() function, and a secondary hash function inside the HashMap/ConcurrentHashMap class (interestingly, the two use different functions). Note that Hashtable and Dictionary (the precursors to HashMap and AbstractMap) are obsolete classes. And a list is really just "something else".
As an example, the String class constructs a hash code by repeatedly multiplying the current code by 31 and adding in the next character. See my article on how the String hash function works for more information. Numbers generally use "themselves" as the hash code; other classes, e.g. Rectangle, that have a combination of fields often use a combination of the String technique of multiplying by a small prime number and adding in, but add in the various field values. (Choosing a prime number means you're unlikely to get "accidental interactions" between certain values and the hash code width, since they don't divide by anything.)
Since the hash table size-- i.e. the number of "buckets" it has-- is a power of two, a bucket number is derived from the hash code essentially by lopping off the top bits until the hash code is in range. The secondary hash function protects against hash functions where all or most of the randomness is in those top bits, by "spreading the bits around" so that some of the randomness ends up in the bottom bits and doesn't get lopped off. The String hash code would actually work fairly well without this mixing, but user-created hash codes may not work quite so well. Note that if two different hash codes resolve to the same bucket number, Java's HashMap implementations use the "chaining" technique-- i.e. they create a linked list of entries in each bucket. It's thus important for hash codes to have a good degree of randomness so that items don't cluster into a particular range of buckets. (However, even with a perfect hash function, you will still by law of averages expect some chaining to occur.)
Hash code implementations shouldn't be a mystery. You can look at the hashCode() source for any class you choose.

The HASHING algorithm is the algorithm used to determine the hash code of an item within the HashTable.
The HASHTABLE algorithm (which I think is what this person is asking) is the algorithm the HashTable uses to organize its elements given their hash code.
Java happens to use a chained hash table algorithm.

While looking for the same answer myself, I found this in .net's reference source # http://referencesource.microsoft.com.
/*
Implementation Notes:
The generic Dictionary was copied from Hashtable's source - any bug
fixes here probably need to be made to the generic Dictionary as well.
This Hashtable uses double hashing. There are hashsize buckets in the
table, and each bucket can contain 0 or 1 element. We a bit to mark
whether there's been a collision when we inserted multiple elements
(ie, an inserted item was hashed at least a second time and we probed
this bucket, but it was already in use). Using the collision bit, we
can terminate lookups & removes for elements that aren't in the hash
table more quickly. We steal the most significant bit from the hash code
to store the collision bit.
Our hash function is of the following form:
h(key, n) = h1(key) + n*h2(key)
where n is the number of times we've hit a collided bucket and rehashed
(on this particular lookup). Here are our hash functions:
h1(key) = GetHash(key); // default implementation calls key.GetHashCode();
h2(key) = 1 + (((h1(key) >> 5) + 1) % (hashsize - 1));
The h1 can return any number. h2 must return a number between 1 and
hashsize - 1 that is relatively prime to hashsize (not a problem if
hashsize is prime). (Knuth's Art of Computer Programming, Vol. 3, p. 528-9)
If this is true, then we are guaranteed to visit every bucket in exactly
hashsize probes, since the least common multiple of hashsize and h2(key)
will be hashsize * h2(key). (This is the first number where adding h2 to
h1 mod hashsize will be 0 and we will search the same bucket twice).
We previously used a different h2(key, n) that was not constant. That is a
horrifically bad idea, unless you can prove that series will never produce
any identical numbers that overlap when you mod them by hashsize, for all
subranges from i to i+hashsize, for all i. It's not worth investigating,
since there was no clear benefit from using that hash function, and it was
broken.
For efficiency reasons, we've implemented this by storing h1 and h2 in a
temporary, and setting a variable called seed equal to h1. We do a probe,
and if we collided, we simply add h2 to seed each time through the loop.
A good test for h2() is to subclass Hashtable, provide your own implementation
of GetHash() that returns a constant, then add many items to the hash table.
Make sure Count equals the number of items you inserted.
Note that when we remove an item from the hash table, we set the key
equal to buckets, if there was a collision in this bucket. Otherwise
we'd either wipe out the collision bit, or we'd still have an item in
the hash table.
--
*/

Anything purporting to be a HashTable or something like it in .NET does not implement its own hashing algorithm: they always call the object-being-hashed's GetHashCode() method.
There is a lot of confusion though as to what this method does or is supposed to do, especially when concerning user-defined or otherwise custom classes that override the base Object implementation.

For .NET, you can use Reflector to see the various algorithms. There is a different one for the generic and non-generic hash table, plus of course each class defines its own hash code formula.

The .NET Dictionary<T> class uses an IEqualityComparer<T> to compute hash codes for keys and to perform comparisons between keys in order to do hash lookups.
If you don't provide an IEqualityComparer<T> when constructing the Dictionary<T> instance (it's an optional argument to the constructor) it will create a default one for you, which uses the object.GetHashCode and object.Equals methods by default.
As for how the standard GetHashCode implementation works, I'm not sure it's documented. For specific types you can read the source code for the method in Reflector or try checking the Rotor source code to see if it's there.