Incremental updates for efficient bidirectional transformations

Posted on October 6, 2016

\[ \newcommand{\compose}{\cdot} \DeclareMathOperator*{\id}{id} \DeclareMathOperator*{\get}{get} \DeclareMathOperator*{\put}{put} \DeclareMathOperator*{\edit}{edit} \DeclareMathOperator*{\affect}{affect} \newcommand{\apply}{\,} \]

I’m taking a look at the paper with the same title.1


The ultimate goal of our framework is to reduce an update of a (large) structure into one of a (small) delta (…).

Take a source term \(s : S\), and a view \(v = \get s : V\). We consider an edit \(e : E_V \) of the view, given by a function \(\edit e : V \to V\) which performs the edit, as well as a function \(\affect e : V \to V\) which computes a subterm of the view such that the edit is contained in it, in the sense that applying \(\edit e \apply v\) is equal to extracting \(w = \affect e \apply v\), (leaving a hole \(v / w\)) then applying the edit on that subterm \(\edit e \apply w\), and finally putting it back, leaving the context surrounding the hole untouched: \[\edit e \apply v = v / w \lessdot \edit e \apply w.\]

Assuming some more niceness about the \(\get : S \to V\) function, and a corresponding \(\put : V \to S \to S\), we can construct a change-based \(\put_E : E_V \to S \to S\) which exploits the locality of the edit, as given by \(\affect\) to make as local a change as possible to the source term, hopefully with improved performance compared to a simple \(\put\).

However, the paper mentions this in Section 5, bounding the action of an edit to a subterm is sometimes ineffective. For instance, considering a view which is a list, 0 : 1 : 2 : 3 : [], deleting 1 results in the list 0 : 2 : 3 : [], and the smallest affected subterm of the initial list is 1 : 2 : 3 : [], because only tails (and individual elements) are subterms of a list. The issue is that this hardly helps \(\put_E\) perform well, because as far as it can tell, almost the whole list has changed.

Section 5 mentions an ad-hoc extension of contexts for lists, so that we can consider actual sublists as subterms: \[(l_1, l_2) \lessdot l = l_1 \cdot l \cdot l_2.\]


The main construction of the paper stems from the observation that many transformations are contained in a subterm of the view. If it is a list, subterms are suffixes. In a way, the \(\affect\) function points to a subtree which is an upper-bound of the locations where changes can take place.

The extension above is additionally motivated by the fact that a suffix of the list argument is preserved by local operations such as the deletion of an element. Thus, we may try to generalize that with a notion of lower-bounds: subtrees that are only moved by the edit, and left unchanged inside.

I would formalize that as follows. Given a term \(v : V\) and a subterm \(w \preccurlyeq v\), we say that \(e : E_V\) is parametric over \(w\) in \(v\) if:

  1. \(w \preccurlyeq \edit e \apply v\),
  2. \( \forall w’ : V,\; \edit e \apply (v / w \lessdot w’) = (\edit e \apply v) / w \lessdot w’. \)


The deletion of 1 in the list 0 : 1 : 2 : 3 : [] is parametric over 2 : 3 : [].

The transformation of an if expression:

if x
then y
else z

to a case expression:

case x of
  True -> y
  False -> z

is parametric over x, y, and z. Rules of a rewriting system are generally parametric.

Assuming some kind of continuity about \(\get\), perhaps similar to the alignment property discussed in the paper, a parametric view transformation might be convertible to a parametric source transformation.

For instance, on an AST as a view of textual source code, the transformation above corresponds to substituting the tokens of an if expression with those of a case expression, without touching those of their bodies.

We can also consider swapping the case alternatives:

case x of
  False -> z
  True -> y

which corresponds to a similar exchange of text in the source.

That mapping appears straightforward to establish by hand; this suggests a general pattern to bidirectionalize \(\get\) for parametric edits.

  1. Incremental Updates for Efficient Bidirectional Transformations. Wang, M., Gibbons, J. and Wu, N. (ICFP’2011). Available at:↩︎