Contents
Is there a better bound for generating substrings?
The naive algorithm would be to traverse the entire string generating substrings in length 1..n in each iteration, yielding an O (n^2) upper bound. Is a better bound possible? As other posters have said, there are potentially O (n^2) substrings for a given string, so printing them out cannot be done faster than that.
How to generate a set of unique substrings?
Given a string s, what is the fastest method to generate a set of all its unique substrings? Example: for str = “aba” we would get substrs= {“a”, “b”, “ab”, “ba”, “aba”}. The naive algorithm would be to traverse the entire string generating substrings in length 1..n in each iteration, yielding an O (n^2) upper bound.
Are there O ( n ^ 2 ) number of substrings?
There are O (n^2) number of substrings. And if you put O (n^2) number of substrings, for example, set, then set compares O (lgn) comparisons for each string to check if it alrady exists in the set or not. Besides it takes O (n) time for string comparison.
How to split a string into maximum number of unique substrings?
Given string str, the task is to split the string into the maximum number of unique substrings possible and print their count. Split the given string into the substrings “a”, “b”, “ab”, “c” and “cc”. Therefore, the maximum count of unique substrings is 5.
How to find all possible substrings in a string?
What I would like to do is take a string and return all possible substrings that are greater than length 2. So using the welcome example: we el lc co me wel elc lco com ome welc elco lcom come and so on…..
How to generate all possible substrings in Python?
The source code is as below: Here is my code in Python. It generates all possible substrings of any given string. If you pass str_ = “abcdef” to the function, it generates the following results:
Is there an algorithm to find substring in a string?
Understanding this would show us what a careful algorithmic thinker would code even for a small problem like this. This is one of the algorithms which is easy to implement but one needs lot of attention and hard work to understand the algorithm.