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edit distance

6 articles · Page 1 of 1
Java Captain
Java Captain
Sep 19, 2026 · Fundamentals

Dynamic Programming Mastery: 11 Classic Problems Solved with Recurrences & C Code

This article analyzes 11 classic dynamic programming problems including coin change, edit distance, LCS, LIS, maximum subarray, matrix chain multiplication, 0-1 knapsack, constrained shortest path, tiling with state compression, work allocation, and three-pass apple picking, providing recurrence relations, C implementations, and optimization techniques.

0-1 knapsackcoin changedynamic programming
0 likes · 34 min read
Dynamic Programming Mastery: 11 Classic Problems Solved with Recurrences & C Code
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 13, 2024 · Fundamentals

Exploring Diff Algorithms: Edit Distance, Longest Common Subsequence, and Myers Algorithm with TypeScript Implementations

This article examines the principles behind diff tools by implementing three approaches—Levenshtein edit distance, longest common subsequence, and the Myers algorithm—in TypeScript, detailing dynamic-programming solutions, back-tracing techniques, and visualizations to illustrate how strings can be transformed efficiently.

TypeScriptalgorithmdiff
0 likes · 19 min read
Exploring Diff Algorithms: Edit Distance, Longest Common Subsequence, and Myers Algorithm with TypeScript Implementations
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Oct 11, 2023 · Fundamentals

Exploring Diff Algorithms: Shortest Edit Distance, Longest Common Subsequence, and Myers Algorithm with TypeScript Implementations

This article investigates how diff tools work by presenting three algorithmic approaches—shortest edit distance, longest common subsequence, and the Myers algorithm—each explained with dynamic‑programming concepts, back‑tracing techniques, and complete TypeScript code examples.

algorithmdiffedit distance
0 likes · 14 min read
Exploring Diff Algorithms: Shortest Edit Distance, Longest Common Subsequence, and Myers Algorithm with TypeScript Implementations
Programmer DD
Programmer DD
Jul 24, 2019 · Fundamentals

Master Dynamic Programming: From Fibonacci to Knapsack, Levenshtein & LCS in Java

This comprehensive guide explains dynamic programming fundamentals, contrasts it with greedy recursion, and walks through Java implementations for Fibonacci, rod‑cutting, simplified and traditional knapsack, Levenshtein edit distance, and longest common subsequence, highlighting performance gains and reconstruction techniques.

LCSalgorithmdynamic programming
0 likes · 26 min read
Master Dynamic Programming: From Fibonacci to Knapsack, Levenshtein & LCS in Java