Enabling Analysis and Reasoning on Software Systems through Knowledge Graph Representation
Satrio Adi Rukmono, Michel R. V. Chaudron · 2023
This work presents a knowledge-representation-based approach for analysing software systems. Its main components are: a generic and extensible knowledge model, and a knowledge extractor tool that generates instance-level knowledge graphs from software repositories (currently Java). Our knowledge model can be used as a shared data-model in a software analysis pipeline. We illustrate the potential uses of our knowledge representation by performing experimental architecture recovery and identifying design pattern instance. We intend to use our ontology and extraction tool as a partial foundation for automated reasoning on software systems.