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<span class="cline-any cline-neutral"> </span></td><td class="text"><pre class="prettyprint lang-js">/**
* Levenshtein Distance Algorithm
*
* Calculates edit distance between two strings for similarity detection.
*
* @module refactoring/levenshtein
*/
/**
* Calculate Levenshtein distance between two strings.
*
* The Levenshtein distance is the minimum number of single-character edits
* (insertions, deletions, or substitutions) required to change one string into another.
*
* Time complexity: O(m * n) where m and n are string lengths
* Space complexity: O(min(m, n)) using space-optimized approach
*
* @param s1 - First string
* @param s2 - Second string
* @returns Edit distance between the strings
*
* @example
* ```typescript
* levenshtein('health_changed', 'health_change') // 1
* levenshtein('player_died', 'player_dead') // 2
* levenshtein('signal_a', 'signal_b') // 1
* ```
*/
export function <span class="fstat-no" title="function not covered" >levenshtein(</span>s1: string, s2: string): number {
// Optimize: swap if s1 is longer to minimize space usage
<span class="cstat-no" title="statement not covered" > <span class="missing-if-branch" title="if path not taken" >I</span>if (s1.length > s2.length) {</span>
<span class="cstat-no" title="statement not covered" > [s1, s2] = [s2, s1];</span>
}
const len1 = <span class="cstat-no" title="statement not covered" >s1.length;</span>
const len2 = <span class="cstat-no" title="statement not covered" >s2.length;</span>
// Edge cases
<span class="cstat-no" title="statement not covered" > <span class="missing-if-branch" title="if path not taken" >I</span>if (len1 === 0) <span class="cstat-no" title="statement not covered" >return len2;</span></span>
<span class="cstat-no" title="statement not covered" > <span class="missing-if-branch" title="if path not taken" >I</span>if (len2 === 0) <span class="cstat-no" title="statement not covered" >return len1;</span></span>
// Use single row for space optimization (O(n) instead of O(m*n))
let prevRow = <span class="cstat-no" title="statement not covered" >new Array(len1 + 1);</span>
let currRow = <span class="cstat-no" title="statement not covered" >new Array(len1 + 1);</span>
// Initialize first row (distances from empty string)
<span class="cstat-no" title="statement not covered" > for (let i = <span class="cstat-no" title="statement not covered" >0;</span> i <= len1; i++) {</span>
<span class="cstat-no" title="statement not covered" > prevRow[i] = i;</span>
}
// Calculate distances row by row
<span class="cstat-no" title="statement not covered" > for (let j = <span class="cstat-no" title="statement not covered" >1;</span> j <= len2; j++) {</span>
<span class="cstat-no" title="statement not covered" > currRow[0] = j; </span>// Distance from empty string
<span class="cstat-no" title="statement not covered" > for (let i = <span class="cstat-no" title="statement not covered" >1;</span> i <= len1; i++) {</span>
const cost = <span class="cstat-no" title="statement not covered" >s1[i - 1] === s2[j - 1] ? 0 : 1;</span>
<span class="cstat-no" title="statement not covered" > currRow[i] = Math.min(</span>
prevRow[i] + 1, // Deletion
currRow[i - 1] + 1, // Insertion
prevRow[i - 1] + cost // Substitution
);
}
// Swap rows for next iteration
<span class="cstat-no" title="statement not covered" > [prevRow, currRow] = [currRow, prevRow];</span>
}
<span class="cstat-no" title="statement not covered" > return prevRow[len1];</span>
}
/**
* Calculate normalized Levenshtein distance (0.0 - 1.0).
*
* Normalized distance = distance / max(len1, len2)
*
* @param s1 - First string
* @param s2 - Second string
* @returns Normalized distance (0.0 = identical, 1.0 = completely different)
*/
export function <span class="fstat-no" title="function not covered" >normalizedLevenshtein(</span>s1: string, s2: string): number {
const distance = <span class="cstat-no" title="statement not covered" >levenshtein(s1, s2);</span>
const maxLen = <span class="cstat-no" title="statement not covered" >Math.max(s1.length, s2.length);</span>
<span class="cstat-no" title="statement not covered" > return maxLen === 0 ? 0 : distance / maxLen;</span>
}
/**
* Calculate Levenshtein similarity (0.0 - 1.0).
*
* Similarity = 1 - normalized distance
*
* @param s1 - First string
* @param s2 - Second string
* @returns Similarity score (1.0 = identical, 0.0 = completely different)
*/
export function <span class="fstat-no" title="function not covered" >levenshteinSimilarity(</span>s1: string, s2: string): number {
<span class="cstat-no" title="statement not covered" > return 1 - normalizedLevenshtein(s1, s2);</span>
}
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