Improving Size-Change Analysis in Offline Partial Evaluation

TL;DR

This paper enhances size-change analysis techniques for offline partial evaluation of logic programs, improving accuracy and program quality without sacrificing scalability or complexity.

Contribution

It introduces several improvements to size-change analysis inspired by experimental evaluation, increasing analysis accuracy while maintaining scalability.

Findings

Improved analysis accuracy leads to higher quality specialized programs

Maintains the same complexity and scalability as previous methods

Experimental results demonstrate effectiveness of the enhancements

Abstract

Some recent approaches for scalable offline partial evaluation of logic programs include a size-change analysis for ensuring both so called local and global termination. In this work|inspired by experimental evaluation|we introduce several improvements that may increase the accuracy of the analysis and, thus, the quality of the associated specialized programs. We aim to achieve this while maintaining the same complexity and scalability of the recent works.