Pattern matching is a computational technique used in various fields such as computer science, mathematics, and linguistics to identify similarities or patterns within a given set of data. It involves comparing a target pattern against a source pattern to determine if they match or correspond to each other. Pattern matching is commonly used in text processing, data mining, bioinformatics, and natural language processing to search for specific sequences of characters, patterns or structures within a larger dataset. It is also used in software development for tasks such as searching for specific code patterns or syntax within source code. There are various algorithms and techniques used for pattern matching, including brute force, Boyer-Moore, Knuth-Morris-Pratt, and regex (regular expressions). These algorithms help efficiently search for patterns within large datasets by optimizing the search process. Overall, pattern matching plays a crucial role in various fields by enabling researchers and practitioners to identify and extract relevant information from data efficiently.