Is there a diff algorithm that preserves line ownership

Question

My goal is coming up with a script to track the point a line was added, even if the line is subsequently modified or moved around (both of which confuse traditional vcs 'blame' scripts. I've done some minor background research (see bottom) but didn't find anything useful. I have a concept for how to proceed but the runtime would be atrocious (there's a factorial involved).

The two missing features are tracking edited-in-place lines separate from a deletion-and-addition of that line, and tracking entire functions moved around so they're in different hunks. For those experienced with diff but unfamiliar with the terminology, a subsequence is a contiguous group of + or - lines, with a type of either delete (all -), add (all +), or replace (a combination). I need more information, on moves and edit-in-place lines, vaguely alluded to in an entry on c2: DiffAlgorithm (paragraph starts with "My favorite mode"). Does anyone know what that is? (seems to be based on Tichy, see bottom.)

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Here's more info on the two missing features:

1. no concept of a change on a line, (a fourth type, something like edit-in-place). In this hunk, the parent of 'bc' is 'b' but 'd' is new and isn't a descendant of 'b':

 a
-b
+bc
+d

The workaround for this isn't too complicated, if the position of edits is the same (just an expanded version of markup_instraline_changes but comparing edit distance on all equal-sized subsets of old and new lines.

1. no concept of "moving" code that preserves the ownership of the lines, e.g. this diff shouldn't alter the ownership of "line", although its position changes.

 a
-line
 c
+line

This could be dealt with in the same way but with much worse runtime (instead of only checking single blocks marked 'replace', you'd need to check Levenshtein distance between all added against all removed lines) and with likely false positives (some, like whitespace-only lines, aren't relevant to my problem).

Research I've done: reading about gestalt pattern matching (Ratcliff and Obershelp, used in Python's difflib) and An O(ND) Difference Algorithm and its Variations (EW Myers).

After posting the question, I found references to Tichy84 which appears to be The string-to-string correction problem with block moves (which I haven't read yet) according to Walter Tichy's paper a year later on RCS

Answer 1

You appear to be interested in origin tracking, the problem of tracing where a line came from.

Ideally, you'd instrument the editor to remember how things were edited, and store the edits with the text in your repository, thus solving the problem trivially, but none of us software engineers seem to be smart enough to implement this simple idea.

As a weak substitute, one can look at a sequence of source code revisions from the repository and reconstruct a "plausible" history of changes. This is what you seem to be doing by proposing the use of "diff". As you've noted, diff doesn't understand the idea of "moving" or "copying".

SD Smart Differencer tools compare source text by parsing the text according to the langauge it is in, discovering the code structures, and computing least-Levensthein differences in terms of programming language constructs (identifiers, expressions, statements, blocks, classes, ...) and abstract editing operators "insert", "delete", "copy", "move" and "rename identifier within a scope". They produce diff-like output, a little richer because they tell you line/column -> line/column with different editing operations.

Obviously the "move" and "copy" edits are the ones most interesting to you in terms of tracking specific lines (well, specific language constructs). Our experience is that code goes through lots of copy and edits, too, which I suspect won't surprise you.

These tools are in Beta, and are presently available for COBOL, Java and C#. Lots of other langauges are in the pipe, because the SmartDifferencer is built on top of a langauge-parameterized infrastructure, DMS Software Reengineering Toolkit, which has quite a number of already existing, robust langauge grammars.

Answer 2

I think the idea of what amount of editing a line that can be done while it remains a descendent of some previously written line is very subjective, and based on context, both things that a computer cannot work with. You'd have to specify some sort of configurable minimum similarity on lines in your program I think... The other problem is that it is entirely possible for two identical lines to be written completely independently (for example incrementing the value of some variable), and this will be be quite a common thing, so your desired algorithm won't really give truthful or useful information about a line quite often.

I would like to suggest an algorithm for this though (which makes tons of hopefully obvious assumptions by the way) so here goes:

Convert both texts to lists of lines
Copy the lists and Strip all whitespace from inside of each line
Delete blank lines from both lists
Repeat
   Do a Levenshtein distance from the old to new lists ...
    ... keeping all intermediate data
   Find all lines in the new text that were matched with old lines
      Mark the line in both new/old original lists as having been matched
      Delete the line from the new text (the copy)
   Optional: If some matched lines are in a contiguous sequence ...
    ... in either original text assign them to a grouping as well!
Until there is nothing left but unmatchable lines in the new text
Group together sequences of unmatched lines in both old and new texts ...
 ... which are contiguous in the original text
   Attribute each with the line match before and after
Run through all groups in old text
   If any match before and after attributes with new text groups for each
    //If they are inside the same area basically
      Concatenate all the lines in both groups (separately and in order)
         Include a character to represent where the line breaks are
      Repeat
         Do a Levenshtein distance on these concatenations
         If there are any significantly similar subsequences found
          //I can't really define this but basically a high proportion
          //of matches throughout all lines involved on both sides
            For each matched subsequence
               Find suitable newline spots to delimit the subsequence
               Mark these lines matched in the original text
                //Warning splitting+merging of lines possible
                //No 1-to-1 correspondence of lines here!
               Delete the subsequence from the new text group concat
               Delete also from the new text working list of lines
      Until there are no significantly similar subsequences found
Optional: Regroup based on remaining unmatched lines and repeat last step
 //Not sure if there's any point in trying that at the moment
Concatenate the ENTIRE list of whitespaced-removed lines in the old text
Concatenate the lines in new text also (should only be unmatched ones left)
 //Newline character added in both cases
Repeat
   Do Levenshtein distance on these concatenations
   Match similar subsequences in the same way as earlier on
    //Don't need to worry deleting from list of new lines any more though
    //Similarity criteria should be a fair bit stricter here to avoid
    // spurious matchings.  Already matched lines in old text might have 
    // even higher strictness, since all of copy/edit/move would be rare
While you still have matchings

//Anything left unmatched in the old text is deleted stuff
//Anything left unmatched in the new text is newly written by the author
Print out some output to show all the comparing results!

Well, hopefully you can see the basics of what I mean with that completely untested algorithm. Find obvious matches first, and verbatim moves of chunks of decreasing size, then compare stuff that's likely to be similar, then look for anything else which is similar, but both modified and moved: probably just coincidentally similar.

Well, if you try implementing this, tell me how it works out, and what details you changed, and what kind of assignments you made to the various variables involved... I expect there will be some test cases where it works brilliantly and others where it just abyssmally fails due to some massive oversight. The idea is that most stuff will be matched before you get to the inefficient final loop, and indeed the previous one