Year: 2024
Type: conference-paper
Abstract: This paper evaluates the performance of Breadth-First Search (BFS) and Depth-First Search (DFS) algorithms in Neo4j using the Graph Data Science (GDS) and the Awesome Procedures on Cypher (APOC) libraries.We benchmark these algorithms on feature models of varying complexity to assess their efficiency and scalability.Our findings indicate that GDS significantly outperforms APOC in terms of traversal times, particularly for large and complex graphs.This study underscores the importance of algorithm optimization in graph databases and provides insights into practical applications and future directions for improving feature model management in software product lines.
Authors: Hazim Shatnawi, Jamil Saquer
Institutions: George Washington University, Missouri State University
Language: English
Topic: Graph Theory and Algorithms
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4406255336