Edit distance has been extensively studied for the past several years. Nevertheless, no linear-time algorithm is known to compute the edit distance between two strings, or even to approximate it to within a modest factor. Furthermore, for various natural algorithmic problems such as low-distortion embeddings into normed spaces, approximate nearest-neighbor schemes, and sketching algorithms, known results for the edit distance are rather weak.

We develop algorithms that solve gap versions of the edit distance problem: given two strings of length n with the promise that their edit distance is either at most k or greater than \ell, decide which of the two holds.

We present two sketching algorithms for gap versions of edit distance. Our first algorithm solves the k vs. (kn)^{{2 \mathord{\left/ {\vphantom {2 3}} \right. \kern-\nulldelimiterspace} 3}} gap problem, using a constant size sketch. A more involved algorithm solves the stronger k vs. \ell gap problem, where \ell can be as small as O(k²) — still with a constant sketch — but works only for strings that are mildly "non-repetitive".

Finally, we develop an n^{{3 \mathord{\left/ {\vphantom {3 7}} \right. \kern-\nulldelimiterspace} 7}}-approximation quasi-linear time algorithm for edit distance, improving the previous best factor of n^{{3 \mathord{\left/ {\vphantom {3 4}} \right. \kern-\nulldelimiterspace} 4}} [5]; if the input strings are assumed to be non-repetitive, then the approximation factor can be strengthened to n^{{1 \mathord{\left/ {\vphantom {1 3}} \right. \kern-\nulldelimiterspace} 3}}.