Work out levenshtein distance instantly with clear inputs, formula shown and shareable results.
Levenshtein distance is the minimum number of single-character insertions, deletions or substitutions needed to turn one string into another, computed with a dynamic-programming table in O(mn) time. Dividing by the longer length gives a similarity ratio that is comparable across string lengths, which is what fuzzy matching, spell checking and record linkage use as a threshold.
Edit distance recurrence
D(x,y) = min(D(x-1,y) + 1, D(x,y-1) + 1, D(x-1,y-1) + cost) where cost is 0 when the characters match
Damerau-Levenshtein also allows transposing two adjacent characters as a single edit, which better reflects typing errors such as teh for the.
Around 0.85 to 0.9 normalised similarity is a common starting point for names, but always calibrate against a labelled sample because it depends heavily on field length.