Optimizing query execution in large differential factbase

Abstract

Differential factbase is a uniform exchangeable representation supporting efficient querying and manipulation, based on the existing concept of program facts. Such factbase is used to store relevant information of software changes. However, the existing factbase is not designed to scale.

This project explores the creation of a system which utilizes a graph database for the efficient storage of program facts. The program facts were successfully modelled as a graph data model and imported into a graph database. The system provides multiple interfaces for users to interact with the graph database either visually or through REST APIs.

From benchmark results obtained, the querying engine of graph database outperformed the original querying engine of differential factbase in terms of query execution times.