Localized RETE for Incremental Graph Queries with Nested Graph Conditions

TL;DR

This paper introduces a localized, incremental RETE-based algorithm for efficient graph query execution on subgraphs, reducing computational overhead in large graph models, with empirical validation in software development and social network scenarios.

Contribution

It presents a novel extension of the RETE algorithm that supports local, incremental graph queries on subgraphs, improving efficiency over traditional global approaches.

Findings

Significantly reduces memory usage and execution time in favorable cases.

May incur overhead in less favorable scenarios.

Validated with software development and social network data.

Abstract

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. To mitigate the outlined shortcoming, in this article 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. We empirically evaluate the presented approach via experiments inspired by a scenario from software development and with queries and data from 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 overhead in unfavorable cases.