AlgorithmsGraphs and textRuns in your browserReviewed October 1, 2026

Levenshtein Distance (Fuzzy Search) Visualizer

Count the fewest single-letter edits needed to turn one word into another. Interactive step-by-step animation with JavaScript code, complexity and front-end use cases.

Localprivate by defaultFastno sign-up path

Graphs and textTime: O(m × n)Space: O(m × n)

Word 1Word 2

		s	i	t	t	i	n	g

k
i
t
t
e
n

Step 1 / 45

Levenshtein distance counts the fewest single-letter edits (insert, delete, replace) to turn "kitten" into "sitting". It powers typo-tolerant ("fuzzy") search.

JavaScript

1function levenshtein(a, b) {
2  const dp = Array.from({ length: a.length + 1 }, (_, i) => [i]);
3  for (let j = 1; j <= b.length; j++) dp[0][j] = j;
4  for (let i = 1; i <= a.length; i++) {
5    for (let j = 1; j <= b.length; j++) {
6      const cost = a[i - 1] === b[j - 1] ? 0 : 1;
7      dp[i][j] = Math.min(
8        dp[i - 1][j] + 1,
9        dp[i][j - 1] + 1,
10        dp[i - 1][j - 1] + cost
11      );
12    }
13  }
14  return dp[a.length][b.length];
15}

Tip: use the arrow keys to step and the space bar to play or pause.

Loading animation...

Levenshtein Distance (Fuzzy Search) Visualization and Animation

Count the fewest single-letter edits needed to turn one word into another. Build a table whose edges are the cost of inserting or deleting all letters. Each cell is the cheapest of delete, insert or replace/keep from its neighbours. The bottom-right cell is the distance. Time complexity: O(m × n). Space complexity: O(m × n). Typo-tolerant search, 'did you mean', form validation and diff tools.

How to use Levenshtein Distance (Fuzzy Search) Visualizer

Build a table whose edges are the cost of inserting or deleting all letters.
Each cell is the cheapest of delete, insert or replace/keep from its neighbours.
The bottom-right cell is the distance.
Press Play, or step through with the arrow buttons and change the input to see how it reacts.

Questions

What is Levenshtein Distance (Fuzzy Search)?

Count the fewest single-letter edits needed to turn one word into another.

What is the time complexity of Levenshtein Distance (Fuzzy Search)?

Time: O(m × n). Space: O(m × n).

Where do front-end developers use Levenshtein Distance (Fuzzy Search)?

Typo-tolerant search, 'did you mean', form validation and diff tools.

Does this upload my data?

No. This converter runs in your browser for ordinary use, so the input is not sent to a backend by this tool.

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