Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Language design and type systems

Refactoring with ornaments in ML

Participants : Thomas Williams, Didier Rémy.

Thomas Williams and Didier Rémy continued working on ornaments for program refactoring and program transformation in ML. Ornaments have been introduced as a way of describing changes in data type definitions that preserve the recursive structure but can reorganize, add, or drop pieces of data. After a new data structure has been described as an ornament of an older one, the functions that operate on the bare structure can be partially or sometimes totally lifted into functions that operate on the ornamented structure.

This year, Williams and Rémy continued working on the description of the lifting algorithm: using ornament inference, an ML program is first elaborated into a generic program, which can be seen as a template for all possible liftings of the original program. The generic program is defined in a superset of ML. It can then be instantiated with specific ornaments, and simplified back into an ML program. Williams and Rémy studied the semantics of this intermediate language and used it to prove the correctness of the lifting, using logical relations techniques. A paper has been accepted for presentation at POPL 2018 [14]. A research report gives more technical details [30].

On the practical side, several families of case studies have been explored, including refactoring and code specialization, as so as to make certain existing invariants apparent, or so as to use more efficient data structures. We improved the user interface of the prototype implementation so as to make it easier to write useful examples. We are currently developing a new version of the prototype that will handle most of the OCaml language.