 In fact, we can use the Levenshtein distance computing algorithm for "E"("m", "j"), the only difference being that we must initialize the first row with zeros, and save the path of computation, that is, whether we used "E"("i" − 1,"j"), E("i","j" − 1) or "E"("i" − 1,"j" − 1) in computing "E"("i", "j").In the array containing the "E"("x", "y") values, we then choose the minimal value in the last row, let it be "E"("x"2, "y"2), and follow the path of computation backwards, back to the row number 0.If the field we arrived at was "E"(0, "y"1), then "T"["y"1 + 1] ... "T"["y"2] is a substring of T with the minimal edit distance to the pattern "P".