String Manipulation and Matching Algorithms

String manipulation and matching algorithms are essential tools in competitive programming using C++. These algorithms help in solving problems that involve operations on strings such as searching, matching, and manipulation. In this article, we will explore some commonly used algorithms for string manipulation and matching.

String Manipulation

1. Concatenation

The concatenation operation is used to combine two or more strings into a single string. In C++, the + operator can be used for concatenating two strings. For example:

string str1 = "Hello";
string str2 = "World";
string result = str1 + " " + str2; // Resultant string: "Hello World"

2. Substring Extraction

The substring extraction operation involves extracting a portion of a given string. In C++, the substr() function can be used to extract substrings from a string. The function takes two arguments: the starting index and the length of the substring. For example:

string str = "Hello World";
string substr = str.substr(6, 5); // Extract substring from index 6 with length 5
// Resultant substring: "World"

3. String Length

The length of a string can be calculated using the length() or size() function in C++. For example:

string str = "Hello World";
int len = str.length(); // Length of the string: 11

4. String Conversion

String conversion involves converting a string to other data types. In C++, the stoi() function can be used to convert a string to an integer, and the stof() function can be used to convert a string to a floating-point number. For example:

string str = "123";
int num = stoi(str); // Convert string to an integer: 123

String Matching Algorithms

1. Brute Force

The brute force algorithm is a simple and straightforward approach to string matching. It involves checking each position of the text string for a match with the pattern string. If a match is found, it continues comparing subsequent characters. This algorithm has a time complexity of O(mn), where m is the length of the text string and n is the length of the pattern string.

2. Knuth-Morris-Pratt (KMP)

The Knuth-Morris-Pratt algorithm is an efficient algorithm for string matching. It avoids unnecessary comparisons by utilizing the information gained from previous comparisons. The algorithm preprocesses the pattern string to create a prefix function, which helps in finding the next position to compare in case of a mismatch. The time complexity of the KMP algorithm is O(m + n), where m is the length of the text string and n is the length of the pattern string.

3. Rabin-Karp

The Rabin-Karp algorithm is a string matching algorithm that uses hashing to find pattern occurrences in a text string. It calculates the hash value of the pattern and the initial window of the text string. If the hash values match, it performs a character-by-character comparison to ensure the match is not a collision. This algorithm has a time complexity of O(m + n), where m is the length of the text string and n is the length of the pattern string.

Conclusion

String manipulation and matching algorithms are powerful tools for solving problems in competitive programming. Understanding these algorithms can help in efficiently solving string-related problems. The algorithms discussed in this article, including concatenation, substring extraction, string length, and string matching algorithms like brute force, Knuth-Morris-Pratt (KMP), and Rabin-Karp, are fundamental techniques to master in string manipulation and matching.