A Polymorphic Groundness Analysis of Logic Programs

TL;DR

This paper introduces a polymorphic groundness analysis for logic programs that infers parameterized groundness descriptions, enhancing analysis flexibility while maintaining precision, demonstrated through experimental results.

Contribution

It presents a novel polymorphic groundness analysis that generalizes monomorphic analysis with parameterized descriptions, preserving precision across all parameter values.

Findings

Polymorphic analysis matches monomorphic analysis precision.

Prototype implementation demonstrates practical viability.

Analysis handles unknown pre-analysis information effectively.

Abstract

A polymorphic analysis is an analysis whose input and output contain parameters which serve as placeholders for information that is unknown before analysis but provided after analysis. In this paper, we present a polymorphic groundness analysis that infers parameterised groundness descriptions of the variables of interest at a program point. The polymorphic groundness analysis is designed by replacing two primitive operators used in a monomorphic groundness analysis and is shown to be as precise as the monomorphic groundness analysis for any possible values for mode parameters. Experimental results of a prototype implementation of the polymorphic groundness analysis are given.