(a, b)
| 10 | */ |
| 11 | |
| 12 | const levenshteinDistance = (a, b) => { |
| 13 | // Declaring array 'D' with rows = len(a) + 1 and columns = len(b) + 1: |
| 14 | const distanceMatrix = Array(b.length + 1) |
| 15 | .fill(null) |
| 16 | .map(() => Array(a.length + 1).fill(null)) |
| 17 | |
| 18 | // Initializing first column: |
| 19 | for (let i = 0; i <= a.length; i += 1) { |
| 20 | distanceMatrix[0][i] = i |
| 21 | } |
| 22 | |
| 23 | // Initializing first row: |
| 24 | for (let j = 0; j <= b.length; j += 1) { |
| 25 | distanceMatrix[j][0] = j |
| 26 | } |
| 27 | |
| 28 | for (let j = 1; j <= b.length; j += 1) { |
| 29 | for (let i = 1; i <= a.length; i += 1) { |
| 30 | const indicator = a[i - 1] === b[j - 1] ? 0 : 1 |
| 31 | // choosing the minimum of all three, vis-a-vis: |
| 32 | distanceMatrix[j][i] = Math.min( |
| 33 | distanceMatrix[j][i - 1] + 1, // deletion |
| 34 | distanceMatrix[j - 1][i] + 1, // insertion |
| 35 | distanceMatrix[j - 1][i - 1] + indicator // substitution |
| 36 | ) |
| 37 | } |
| 38 | } |
| 39 | |
| 40 | return distanceMatrix[b.length][a.length] |
| 41 | } |
| 42 | |
| 43 | export { levenshteinDistance } |
no outgoing calls
no test coverage detected