  The problem of approximate string matching is important in many different
areas such as computational biology, text processing and pattern recognition. A
great effort has been made to design efficient algorithms addressing several
variants of the problem, including comparison of two strings, approximate
pattern identification in a string or calculation of the longest common
subsequence that two strings share.
  We designed an output sensitive algorithm solving the edit distance problem
between two strings of lengths n and m respectively in time
O((s-|n-m|)min(m,n,s)+m+n) and linear space, where s is the edit distance
between the two strings. This worst-case time bound sets the quadratic factor
of the algorithm independent of the longest string length and improves existing
theoretical bounds for this problem. The implementation of our algorithm excels
also in practice, especially in cases where the two strings compared differ
significantly in length. Source code of our algorithm is available at
http://www.cs.miami.edu/\~dimitris/edit_distance
