As mentioned briefly in the previous section, there are multiple ways for
constructing a hash function. Remember that hash function takes the data as
input (often a string), and return s an integer in the range of possible
indices into the hash table. Every hash function must do that, including
the bad ones. So what makes for a good hash function?

###
Characteristics of a Good Hash Function

There are four main characteristics of a good hash function:
1) The hash value is fully determined by the data being hashed.
2) The hash function uses all the input data.
3) The hash function "uniformly" distributes the data across the entire set
of possible hash values.
4) The hash function generates very different hash values for similar strings.

Let's examine why each of these is important:
Rule 1: If something else besides the input data is used to determine the
hash, then the hash value is not as dependent upon the input data, thus
allowing for a worse distribution of the hash values.
Rule 2: If the hash function doesn't use all the input data, then slight
variations to the input data would cause an inappropriate number of similar
hash values resulting in too many collisions.
Rule 3: If the hash function does not uniformly distribute the data across
the entire set of possible hash values, a large number of collisions will
result, cutting down on the efficiency of the hash table.
Rule 4: In real world applications, many data sets contain very similar
data elements. We would like these data elements to still be distributable
over a hash table.

So let's take as an example the hash function used in the last section:

`
int hash(char *str, int table_size)
{
int sum;
// Make sure a valid string passed in
if (str==NULL) return -1;
// Sum up all the characters in the string
for( ; *str; str++) sum += *str;
// Return the sum mod the table size
return sum % table_size;
}
`

Which rules does it break and satisfy?
Rule 1: Satisfies. The hash value is fully determined by the data being
hashed. The hash value is just the sum of all the input characters.
Rule 2: Satisfies. Every character is summed.
Rule 3: Breaks. From looking at it, it isn't obvious that it doesn't
uniformly distribute the strings, but if you were to analyze this function
for a large input you would see certain statistical properties bad for a
hash function.
Rule 4: Breaks. Hash the string "bog". Now hash the string "gob". They're
the same. Slight variations in the string should result in different hash
values, but with this function they often don't.

So this hash function isn't so good. It's a good introductory example but
not so good in the long run.