{
  "id": 17909104,
  "title": "Inside the Myers Diff Algorithm: How Git Finds Code Changes (And How to Build One in Vanilla JS)",
  "url": "https://urgent.news/2026/11/03/inside-the-myers-diff-algorithm-how-git-finds-code-changes-and-how-to",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-03T04:40:20.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/urbanmixo/inside-the-myers-diff-algorithm-how-git-finds-code-changes-and-how-to-build-one-in-vanilla-js-2akk"
  },
  "original_language": "en",
  "account": "In Eugene Myers' 1986 diff algorithm, the process of finding code changes in files is transformed into a classic graph search problem on a 2D Cartesian coordinate plane. This approach allows for an efficient solution to identify the shortest sequence of edits—known as the Shortest Edit Script (SES)—required to transform one file into another.\n\nTo begin, consider two sequences: Original (A) with seven lines [A, B, C, A, B, B, A] and Modified (B) with six lines [C, B, A, B, A, C]. These sequences are represented as an (N + 1) x (M + 1) grid, where the x-axis represents lines in the original file A and the y-axis represents lines in the modified file B.\n\nThe search starts at the top-left origin (0, 0) and must reach the bottom-right terminal (N, M). The three rules of movement in this graph are:\n\n1. Move Right (x + 1): Deletes a line from the original file A. This operation costs 1 edit.\n2. Move Down (y + 1): Inserts a line from the modified file B. This operation also costs 1 edit.\n3. Move Diagonally (x + 1, y + 1): Occurs when line A[x] matches line B[y]. This operation costs 0 edits, as the lines are identical.\n\nThe goal is to find the shortest path from (0, 0) to (N, M) while taking advantage of as many free diagonal shortcuts as possible. This is mathematically equivalent to finding the shortest path in the graph search problem.\n\nTo implement the LCS algorithm, a dynamic programming baseline is used. The LCS matrix is computed using typed arrays for efficient memory locality. The matrix is filled with the length of the longest common subsequence between the two sequences, and a backtracking process is performed to assemble the shortest edit script.\n\nBy understanding the graph theory behind Myers' diff algorithm and implementing it in vanilla JavaScript, it is possible to build a zero-dependency diff engine in the browser. This allows software engineers to have a deeper understanding of how their version control system identifies changes in code files.",
  "summary": "Inside the Myers Diff Algorithm: How Git Finds Code Changes (And How to Build One in Vanilla JS) Every single day, millions of software engineers run git diff , inspect pull requests on GitHub, or review merge conflicts in VS Code. We take for granted that when we modify a 2,000-line file, our version control system instantly identifies: The exact three lines we deleted (highlighted in red with a…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}