Detecting Performance Anti-patterns for Applications Developed using Object-Relational Mapping

Object-Relational Mapping (ORM) provides developers a conceptual abstraction for mapping the application code to the underlying databases. ORM is widely used in industry due to its convenience; permitting developers to focus on de-veloping the business logic without worrying too much about the database access details. However, developers often write ORM code without considering the impact of such code on database performance, leading to cause transactions with timeouts or hangs in large-scale systems. Unfortunately, there is little support to help developers automatically de-tect suboptimal database accesses. In this paper, we propose an automated framework to de-tect ORM performance anti-patterns. Our framework auto-matically flags performance anti-patterns in the source code. Furthermore, as there could be hundreds or even thousands of instances of anti-patterns, our framework provides sup-port to prioritize performance bug fixes based on a statis-tically rigorous performance assessment. We have success-fully evaluated our framework on two open source and one large-scale industrial systems. Our case studies show that our framework can detect new and known real-world perfor-mance bugs and that fixing the detected performance anti-patterns can improve the system response time by up t