Structured Traversal of Search Trees in Constraint-logic Object-oriented Programming

TL;DR

This paper introduces an explicit, non-strict search tree representation in constraint-logic object-oriented programming, enabling flexible search strategies and demonstrating their implementation and comparison within the Muli language.

Contribution

It presents a novel explicit search tree model for constraint-logic OOP, allowing on-demand traversal strategies like breadth-first and iterative deepening, which were not previously available.

Findings

Implemented three search algorithms: depth-first, breadth-first, iterative deepening.

Enabled complete search strategies in constraint-logic object-oriented programming.

Compared search strategies using benchmarks to evaluate performance.

Abstract

In this paper, we propose an explicit, non-strict representation of search trees in constraint-logic object-oriented programming. Our search tree representation includes both the non-deterministic and deterministic behaviour during execution of an application. Introducing such a representation facilitates the use of various search strategies. In order to demonstrate the applicability of our approach, we incorporate explicit search trees into the virtual machine of the constraint-logic object-oriented programming language Muli. We then exemplarily implement three search algorithms that traverse the search tree on-demand: depth-first search, breadth-first search, and iterative deepening depth-first search. In particular, the last two strategies allow for a complete search, which is novel in constraint-logic object-oriented programming and highlights our main contribution. Finally, we compare the implemented strategies using several benchmarks.