NODES 2024 – Detecting and Mapping Code Defects Introduced by Generative AI Using CodeLogic & Neo4j

Making informed development decisions requires a strong understanding of the connections and complexity within and across your application landscape. With generative AI enabling software changes faster than ever, and dozens of applications to manage within a single enterprise, it is often difficult to have a clear view of how everything fits together. CodeLogic equips engineers with the most comprehensive software dependency data available, combining artifact and runtime scanning to create a complete graph of an enterprise’s application structures.

In this session, you will learn how CodeLogic utilizes Neo4j and CypherQL to detect breaking code changes introduced by generative AI and how they can be addressed before a change is accepted into mainline development. Attendees will learn a rare use case for graph and see how CodeLogic models data into simplified maps that can be easily analyzed to identify cross-application dependencies, navigate code change impact, and ultimately reveal the bigger picture.

with Brandon Tylke, Edwin Gnichtel

Get certified with GraphAcademy: https://dev.neo4j.com/learngraph
Neo4j AuraDB https://dev.neo4j.com/auradb
Knowledge Graph Builder https://dev.neo4j.com/KGBuilder
Neo4j GenAI https://dev.neo4j.com/graphrag