Whenever a feature is looked up in a dictionary, the result is stored in an instance of this class. In general, the result doesn't contain only the most similar feature. Much more, it contains a certain amount of similar features ordered by distance.

Besides other access possibilities, instances of this class provide an iterator to iterate through the result.

	copying
	copy

	initialize-release
	initializeDictionary:minSize:

	private
	isAvailable: isDistinctCharAvailable: isWorseThanDistance:difference:relativeDifference:

	testing
	isAlert: isReject:

	accessing	top
	add: Add a new lookup item to the result
	addFeature:char:distance: Construct new lookup item and add to result
	addResult: Add all the items of the other result to this result
	at: Answer my element at index anInteger. at: is used by a knowledgeable client to access an existing element
	char return character at iterator position
	charAt:
	charType Return type of character at iterator position
	charTypeAt:
	copyWithoutParentFeatures Copy the result and eliminate all the features that are not in the base dictionary
	correspondingKeystrokes Return the corredponsing keystrokes of the charater at the iterator position
	correspondingKeystrokesAt:
	correspondingMouseEventsHand:position:buttons:
	correspondingMouseEventsHand:position:buttons:at:
	correspondsToKeystrokes Does the character at the iterator positon correspond to a keystroke?
	correspondsToKeystrokesAt:
	correspondsToMouseEvents Does the character at the iterator position corrpesond to a mouse event?
	correspondsToMouseEventsAt:
	dictionary
	dictionary:
	distance Return the distance at the iterator position
	distanceAt:
	distanceDifference Distance difference between best and second best match
	distanceDifferenceFrom:to: Distance difference between two matches identified by their position.
	distanceDifferenceFrom:toDistinctChar: Distance between two matches with different assigned characters!
	distanceDifferenceToDistinctChar Distance from the best match to the next best feature that is associated to a distinct character
	distinctCharItem: Return the item of the n-th dictinct character
	distinctCharSize Number of matches with dictinct characters
	eliminateParentFeatures Eliminate all the features that are not included in the dictionary
	evaluateCodeIn: Evaluate the code of the character at the current iterator position
	evaluateCodeIn:at:
	feature Feature at the iterator position
	featureAt:
	indexOfDistinctChar: Index of the n-th distinct char
	indexOfDistinctChar:startAt: Index of the n-th dictinct char from startInteger
	isCode Is character at interator position code?
	isCodeAt:
	isCommand Is character at interator position command?
	isCommandAt:
	isStrokes Is character at interator position strokes?
	isStrokesAt:
	lookupIndex Iterator position
	lookupIndex: iterator position
	minSize Minimum size (number of matches) of the result
	minSize: Minimum size (number of matches) of the result
	nextDistinctCharMatch Move the iterator to the next dictinct character
	nextDistinctCharMatchRollover: Move the iterator to the next dictinct character
	nextMatch Move the iterator to the next match
	nextMatchRollover: Move the iterator to the next match
	normalizedCharAt:
	relativeDistanceDifference
	relativeDistanceDifferenceFrom:to: Relative distance between two matches
	relativeDistanceDifferenceFrom:toDistinctChar:
	relativeDistanceDifferenceToDistinctChar

	copying	top
	copy Answer another instance just like the receiver. Subclasses typically override this method; they typically do not override shallowCopy.

	initialize-release	top
	initializeDictionary:minSize:

	private	top
	isAvailable: Does the instance contain at least indexNumber features?
	isDistinctCharAvailable: Does the instance contain at least indexNumber features that are assigned to a distinct character? (Features assigned to the same character count only once)
	isWorseThanDistance:difference:relativeDifference: Determines wheter the lookup suffice to the given quality requirements: 1) The distance to the best match must be no more than distanceNumber (distanceNumber is given in percent of the maximum distance). 2) The distance between the best and the second best match must be bigger than diffNumber (distanceNumber is given in percent of the maximum distance) OR: The relative distance from the best to the second best match must be bigger than relDiffNumber (relDiffNumber is given in percent).

	testing	top
	isAlert: Is match so bad (ambiguous) that user should be warned?
	isReject: Is match too bad (ambiguous) to be accepted?

	instance creation	top
	dictionary:
	dictionary:minSize: