This is one of the questions in the Cracking the Coding Interview book by Gayle Laakmann McDowell:
Implement an algorithm to determine if a string has all unique characters. What if you can not use additional data structures?
The author wrote:
We can reduce our space usage a little bit by using a bit vector. We will assume, in the below code, that the string is only lower case
'a'
through'z'
. This will allow us to use just a single int.
The author has this implementation:
public static boolean isUniqueChars(String str) {
int checker = 0;
for (int i = 0; i < str.length(); ++i) {
int val = str.charAt(i) - 'a';
if ((checker & (1 << val)) > 0)
return false;
checker |= (1 << val);
}
return true;
}
Let's say we get rid of the assumption that "the string is only lower case 'a'
through 'z'
". Instead, the string can contain any kind of character—like ASCII characters or Unicode characters.
Is there a solution as efficient as the author's (or a solution that comes close to being as efficient as the author's)?
Related questions:
- Detecting if a string has unique characters: comparing my solution to "Cracking the Coding Interview?"
- Explain the use of a bit vector for determining if all characters are unique
- String unique characters
- Implementing an algorithm to determine if a string has all unique characters
- determine if a string has all unique characters?
for the asccii character set you can represent the 256bits in 4 longs: you basically hand code an array.
You can use the following code to generate the body of a similar method for unicode characters:
I think we need a general and practical definition of "additional data structures". Intuitively, we don't want to call every scalar integer or pointer a "data structure", because that makes nonsense of any prohibition of "additional data structures".
I propose we borrow a concept from big-O notation: an "additional data structure" is one that grows with the size of the data set.
In the present case, the code quoted by the OP appears to have a space requirement of O(1) because the bit vector happens to fit into an integer type. But as the OP implies, the general form of the problem is really O(N).
An example of a solution to the general case is to use two pointers and a nested loop to simply compare every character to every other. The space requirement is O(1) but the time requirement is O(N^2).
You only need one line... well less than one line actually:
this uses a negative look ahead to assert that each character is not repeated later in the string.
This approach a time complexity of O(n^2), because for all n characters in the input, all characters that follow (there are n of those) are compared for equality.
How about the following algorithm?
Steps:
Convert string to lowercase.
Loop through each character in the string
Set variable data = 0
Calculate offset = ascii value of first character in string - 97
Set the flag for that position with mask = 1 << offset
If bitwise AND returns true, then a character is repeating (mask & data), so break here.
else if we have not seen the character repeat yet, set the bit for that character by doing a bitwise OR by doing data = data | mask
Continue till end of characters.