This is a fairly simple Awk script to analyze one or more text files and report on matches or near-matches. It uses the Levenshtein distance algorithm to perform fuzzy matches on lines of text.

It generates a report, showing matches and the score for each. The minimum score can be adjusted on the command line. You can use the report to find strings to reuse, or catch inconsistencies.

Use plain text, stripped of all markup. Each line should be a single sentence or block (paragraph). For DITA, use a script like this to prepare your text (requires the org.lwdita plugin):

dita --format=markdown_github --input=my.bookmap --args.rellinks=none
cd out
rm index.md
for i in *.txt; do
	f=`basename $i .md`
	pandoc -t plain —wrap=none -o $f.txt $i
done

This puts each block element on a single line.

For word processor documents, save as text.

Use this command to run the script:

awk -f analyzer.awk [-v option=value]... files...

You can specify multiple options. Available options are:

minratio (default: 0.95) : The minimum fuzzy matching ratio to report on. A value of 1 turns off fuzzy matching, reporting only exact matches.

minlength (default: 0) : The minimum string length to compare.

ignorecase (default: 0) : Set to 1 to make matching case-insensitive.

quiet (default: 0) : Set to 1 to suppress status and progress messages.

progress (default: 100) : Prints a status/progress message after comparing this many blocks.

Fuzzy matching is a processor-intensive activity, especially when using a script. Limiting the number of matches needed is the most effective strategy to improve performance. The script uses these techniques to avoid doing fuzzy matches:

• Blocks (lines of text) are not compared to themselves.
• After comparing a block to everything else, the analyzer throws out the block to avoid duplicate comparisons. This by itself cuts runtime in half.
• If two blocks have a length different enough that the result could never reach minratio, they are not compared. This makes a big difference in the time needed.
• The script checks for an exact match before attempting the fuzzy match.

A small to mid-size document set (about 2200 paragraphs) takes just under 5 minutes to analyze on a late-2013 iMac. You can compile the script, using awka, for a performance boost (the same document set takes 1-1/2 minutes with the compiled version). To compile the script, use:

awka -X -f analyzer.awk
mv awka.out analyzer

Commercial reuse analyzers tend to have nicer interfaces, and some meant for DITA can build a collection (or library) file of strings and automatically apply them to your topics.

On the other hand, if your budget is very limited and you have a small document set to analyze, this one might be exactly what you need.