Longest substring without repeating characters is a common problem in computer science that can be solved using various algorithms. One of the most popular solutions is using the sliding window technique in C++. This method is efficient and easy to implement, making it a preferred choice for many programmers. In this article, we will discuss the sliding window technique and its implementation in C++.
A substring is a continuous sequence of characters within a larger string. The longest substring without repeating characters is the substring that contains the most characters without any repeating characters. This problem can be solved by using the sliding window technique, which is a method that uses two pointers to keep track of the substring. The first pointer is called the left pointer, and the second pointer is called the right pointer. The left pointer represents the start of the substring, and the right pointer represents the end of the substring.
The sliding window technique works by moving the right pointer to the right and adding each character to the substring. If a repeating character is encountered, the left pointer is moved to the right until the repeating character is removed from the substring. This process is repeated until the right pointer reaches the end of the string. The substring that contains the most characters without any repeating characters is the longest substring without repeating characters.
The implementation of the sliding window technique in C++ is straightforward. The first step is to initialize the left and right pointers to 0. Then, the right pointer is moved to the right, and each character is added to the substring. If a repeating character is encountered, the left pointer is moved to the right until the repeating character is removed from the substring. This process is repeated until the right pointer reaches the end of the string.
The following is an example of the sliding window technique implemented in C++:
int lengthOfLongestSubstring(string s) { unordered_map<char, int> charMap; int maxLength = 0; int left = 0; for (int right = 0; right < s.length(); right++) { if (charMap.count(s[right]) && charMap[s[right]] >= left) { left = charMap[s[right]] + 1; } charMap[s[right]] = right; maxLength = max(maxLength, right - left + 1); } return maxLength; }
In this example, the lengthOfLongestSubstring function takes a string as input and returns the length of the longest substring without repeating characters. The unordered_map data structure is used to keep track of the characters in the substring. The left and right pointers are initialized to 0, and the right pointer is moved to the right, adding each character to the substring. If a repeating character is encountered, the left pointer is moved to the right until the repeating character is removed from the substring. The maxLength variable is used to keep track of the length of the longest substring without repeating characters.
It is important to note that the sliding window technique has a time complexity of O(n), where n is the length of the string. This makes it an efficient solution for solving the longest substring without repeating characters problem. The use of the unordered_map data structure also improves the efficiency of the algorithm by reducing the time complexity to O(1) for searching for repeating characters.
In conclusion, the sliding window technique is a popular and efficient solution for solving the longest substring without repeating characters problem. The implementation in C++ is straightforward and easy to understand
