readme.md

Original Reference:
http://www.merriampark.com/ldobjc.htm

Store & Sort Matches Based on Search String

	NSMutableArray *results = [NSMutableArray array];
	
	for (id item in theItemList) {
		// note the modified weighting, this ends up working similiar to Alfred / TextMate searching method
		// TextMate takes into account camelcase while matching and is a little smarter, but you get the idea
		NSInteger score = [_searchString compareWithWord:[item searchOnString] matchGain:10 missingCost:1];
		
		[results addObject:[NSDictionary dictionaryWithObjectsAndKeys:[NSNumber numberWithInteger:score], @"score", list, @"item", nil]];
	}
	
	// sort list
	results = [results sortedArrayUsingComparator: (NSComparator)^(id obj1, id obj2) {
		return [[obj1 valueForKey:@"score"] compare:[obj2 valueForKey:@"score"]];
	}];g

Note:

• The compareWithString: has not been tested extensively.
• 64bit compatible
• There are a couple more modifications / tweaks from the original, look at revision history for details

NSString+Levenshtein.h

//
//  NSString+Levenshtein.h
//  PyHelp
//
//  Modified by Michael Bianco on 12/2/11.
//	<http://mabblog.com>
//
//  Created by Rick Bourner on Sat Aug 09 2003.
//  rick@bourner.com

#import <Foundation/Foundation.h>

@interface NSString (Levenshtein)

// calculate the smallest distance between all words in stringA and stringB
- (CGFloat) compareWithString: (NSString *) stringB matchGain:(NSInteger)gain missingCost:(NSInteger)cost;

// calculate the distance between two string treating them each as a single word
- (NSInteger) compareWithWord:(NSString *) stringB matchGain:(NSInteger)gain missingCost:(NSInteger)cost;
@end

NSString+Levenshtein.m

//
//  NSString+Levenshtein.m
//  PyHelp
//
//  Modified by Michael Bianco on 12/2/11.
//	<http://mabblog.com>
//
//  Created by Rick Bourner on Sat Aug 09 2003.
//  rick@bourner.com

#import "NSString+Levenshtein.h"

@implementation NSString (Levenshtein)

// default match: 0
// default cost: 1

// calculate the mean distance between all words in stringA and stringB
- (CGFloat) compareWithString: (NSString *) stringB matchGain:(NSInteger)gain missingCost:(NSInteger)cost {
	CGFloat averageSmallestDistance = 0.0;
	CGFloat smallestDistance;
	
	NSString *mStringA = [self stringByReplacingOccurrencesOfString:@"\n" withString:@" "];
	NSString *mStringB = [stringB stringByReplacingOccurrencesOfString:@"\n" withString:@" "];
	
	NSArray *arrayA = [mStringA componentsSeparatedByString: @" "];
	NSArray *arrayB = [mStringB componentsSeparatedByString: @" "];
	
	for (NSString *tokenA in arrayA) {
		smallestDistance = 99999999.0;
		
		for (NSString *tokenB in arrayB) {
			smallestDistance = MIN((CGFloat) [tokenA compareWithWord:tokenB matchGain:gain missingCost:cost], smallestDistance);
		}
		
		averageSmallestDistance += smallestDistance;
	}
	
	return averageSmallestDistance / (CGFloat) [arrayA count];
}


// calculate the distance between two string treating them eash as a single word
- (NSInteger) compareWithWord:(NSString *) stringB matchGain:(NSInteger)gain missingCost:(NSInteger)cost {
	// normalize strings
	NSString * stringA = [NSString stringWithString: self];
	stringA = [[stringA stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceAndNewlineCharacterSet]] lowercaseString];
	stringB = [[stringB stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceAndNewlineCharacterSet]] lowercaseString];	
	
	// Step 1
	NSInteger k, i, j, change, *d, distance;
	
	NSUInteger n = [stringA length];
	NSUInteger m = [stringB length];	
	
	if( n++ != 0 && m++ != 0 ) {
		d = malloc( sizeof(NSInteger) * m * n );
		
		// Step 2
		for( k = 0; k < n; k++)
			d[k] = k;
		
		for( k = 0; k < m; k++)
			d[ k * n ] = k;
		
		// Step 3 and 4
		for( i = 1; i < n; i++ ) {
			for( j = 1; j < m; j++ ) {
				
				// Step 5
				if([stringA characterAtIndex: i-1] == [stringB characterAtIndex: j-1]) {
					change = -gain;
				} else {
					change = cost;
				}
				
				// Step 6
				d[ j * n + i ] = MIN(d [ (j - 1) * n + i ] + 1, MIN(d[ j * n + i - 1 ] +  1, d[ (j - 1) * n + i -1 ] + change));
			}
		}
		
		distance = d[ n * m - 1 ];
		free( d );
		return distance;
	}
	
	return 0;
}

@end