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A Hamming distance in information technology represents the number of points at which two corresponding pieces of data can be different. It is often used in various kinds of error correction or evaluation of contrasting strings or pieces of data.
While it may seem complicated and obscure on first glance, the Hamming distance is actually a very practical metric for measuring data strings. The Hamming distance involves counting up which set of corresponding digits or places are different, and which are the same. For example, take the text string “hello world” and contrast it with another text string, “herra poald.” There are five places along the corresponding strings where the letters are different.
Why is this important? One fundamental application of Hamming distance is to correct binary code either toward one result or another. Professionals talk about one-bit errors or two-bit errors, the idea that corrupted data can be transformed into a correct original result. The problem is, if there are two strings and one corrupted piece of data, one must ascertain which final result the corrupted or third data set is closest to. That is where the Hamming distance comes in – for example, if the Hamming distance is four, and there is a one-bit error toward one result, it is most likely that that is the correct result. This is just one of the applications that the Hamming distance can have toward code and data string evaluation.