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The following gives an example for Text edits are based on the Levenshtein algorithm. It “observes” how many keystrokes are required to transform an initial text into the changed text. If a new text has 10 more characters it will assume an edit distance of 10. For a more precise and complete description see the Wikipedia page: Levenshtein algoritm.

The following is an example to demonstrate how the edit distance values properties are calculated in the Text edits report .

Segment

Initial text

Updated text

Edit distance (ED)

Max length (L)

Normalized ED

1

abcd

4 chars

4 chars (maximum of 0 and 4)

1.00 (4 divided by 4)

2

abcd

abcdef

2 chars

6 chars (maximum of 4 and 6)

0.29 (2 divided by 6)

3

abcd

abcd

0 chars

4 chars

0.00 (0 divided by 4)

...