Hamming Distance
Hamming distance is a metric used in information theory, coding theory, and computer science to measure the difference between two strings of equal length. It calculates the number of positions at which the corresponding symbols (e.g., bits, characters) differ between the two strings. This concept is fundamental for error detection and correction, data comparison, and similarity analysis in fields like genetics and cryptography.
Developers should learn Hamming distance when working on error-correcting codes, data validation, or algorithms that require comparing sequences, such as in DNA sequencing, network protocols, or checksum calculations. It is particularly useful in scenarios where bit-level or character-level differences need to be quantified efficiently, such as in parity checks, RAID systems, or string similarity tasks in machine learning and natural language processing.