Source-to-source optimizing transformations of Prolog programs based on abstract interpretation

TL;DR

This paper introduces an abstract interpretation-based optimizer that automatically transforms Prolog source code to improve efficiency while preserving semantics, considering program annotations and input call contexts.

Contribution

It presents a novel method for safe, automatic source-to-source optimization of Prolog programs using abstract interpretation, accommodating program annotations.

Findings

Effective code transformations depend on program annotations.

The optimizer preserves semantics while enhancing efficiency.

Applicable to any Prolog program with annotations.

Abstract

Making a Prolog program more efficient by transforming its source code, without changing its operational semantics, is not an obvious task. It requires the user to have a clear understanding of how the Prolog compiler works, and in particular, of the effects of impure features like the cut. The way a Prolog code is written - e.g., the order of clauses, the order of literals in a clause, the use of cuts or negations - influences its efficiency. Furthermore, different optimization techniques may be redundant or conflicting when they are applied together, depending on the way a procedure is called - e.g., inserting cuts and enabling indexing. We present an optimiser, based on abstract interpretation, that automatically performs safe code transformations of Prolog procedures in the context of some class of input calls. The method is more effective if procedures are annotated with additional information about modes, types, sharing, number of solutions and the like. Thus the approach is similar to Mercury. It applies to any Prolog program, however.