Localized RETE for Incremental Graph Queries

TL;DR

This paper introduces a localized, incremental RETE-based approach for graph queries that improves efficiency when working with subgraphs, reducing memory and time costs in many scenarios.

Contribution

It extends the RETE algorithm to support local, incremental graph query execution, ensuring completeness for subgraphs while enhancing performance.

Findings

Significant reduction in memory usage and execution time in favorable cases

Linear overhead observed in less favorable scenarios

Effective for software development and social network benchmarks

Abstract

Context: The growing size of graph-based modeling artifacts in model-driven engineering calls for techniques that enable efficient execution of graph queries. Incremental approaches based on the RETE algorithm provide an adequate solution in many scenarios, but are generally designed to search for query results over the entire graph. However, in certain situations, a user may only be interested in query results for a subgraph, for instance when a developer is working on a large model of which only a part is loaded into their workspace. In this case, the global execution semantics can result in significant computational overhead. Contribution: To mitigate the outlined shortcoming, in this paper we propose an extension of the RETE approach that enables local, yet fully incremental execution of graph queries, while still guaranteeing completeness of results with respect to the relevant subgraph. Results: We empirically evaluate the presented approach via experiments inspired by a scenario from software development and an independent social network benchmark. The experimental results indicate that the proposed technique can significantly improve performance regarding memory consumption and execution time in favorable cases, but may incur a noticeable linear overhead in unfavorable cases.