The paper "The String-to-String Correction Problem" by Robert A. Wagner and Michael J. Fischer introduces the concept of edit distance, which measures the minimum cost of transforming one string into another through a sequence of edit operations: changing, deleting, or inserting a single character. The authors present an algorithm that efficiently computes this distance in time proportional to the product of the lengths of the two strings. This algorithm has applications in spelling correction and finding the longest common subsequence of characters between two strings. The paper defines traces, which are structures that describe the transformation from one string to another, and uses them to simplify the problem of computing edit distance. The authors also provide algorithms for computing the edit distance and finding the longest common subsequence, both of which are efficient and practical for real-world applications.The paper "The String-to-String Correction Problem" by Robert A. Wagner and Michael J. Fischer introduces the concept of edit distance, which measures the minimum cost of transforming one string into another through a sequence of edit operations: changing, deleting, or inserting a single character. The authors present an algorithm that efficiently computes this distance in time proportional to the product of the lengths of the two strings. This algorithm has applications in spelling correction and finding the longest common subsequence of characters between two strings. The paper defines traces, which are structures that describe the transformation from one string to another, and uses them to simplify the problem of computing edit distance. The authors also provide algorithms for computing the edit distance and finding the longest common subsequence, both of which are efficient and practical for real-world applications.