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I have the following task: developing a program where there is a block of sample text which should be typed by user. Any typos the user does during the test are registered. Basically, I can compare each typed char with the sample char based on caret index position of the input, but there is one significant flaw in such a "naive" approach. If the user typed mistakenly more letters than a whole string has, or inserted more white spaces between the string than should be, then the rest of the comparisons will be wrong because of the index offsets added by the additional wrong insertions.

I have thought of designing some kind of parser where each string (or even a char ) is tokenized and the comparisons are made "char-wise" and not "index-wise," but that seems to me like an overkill for such a task. I would like to get a reference to possibly existing algorithms which can be helpful in solving this kind of problem.

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It sounds like what you need is equivalent to doing a 'diff' on two files. There are many ways to do this, but I'd look into Google's diff-match-patch algorithm.

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Pretty much the only way to do this is to use grapheme clusters and then compare their normalized versions.

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    Could you extend on this a little bit? – Michael IV Mar 2 '13 at 17:51

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