Neo4j’s BFS and DFS Evaluation in GDS and APOC Libraries with SPL Feature Models
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.
Department(s)
Computer Science
Document Type
Conference Proceeding
DOI
10.18293/SEKE2024-110
Keywords
directed acyclic graphs, graph databases, Neo4j, software product lines, traversal algorithms in graph data science
Publication Date
1-1-2024
Recommended Citation
Saquer, Jamil M. and Shatnawi, Hazim, "Neo4j’s BFS and DFS Evaluation in GDS and APOC Libraries with SPL Feature Models" (2024). Faculty Scholarship. 472.
https://bearworks.missouristate.edu/articles00/472
Journal Title
Proceedings of the International Conference on Software Engineering and Knowledge Engineering Seke
