Investigating AI for Software Performance Engineering

Performance is a critical non-functional aspect of modern software systems. Ensuring efficiency necessitates rigorous performance assurance throughout the entire software lifecycle, from early development to post-deployment. However, as system complexity continues to grow, this task becomes increasingly challenging. In this context, automation is pivotal in accelerating performance assurance activities and reducing the associated costs. By leveraging large-scale data and advanced predictive models, AI-driven approaches have demonstrated their effectiveness in a variety of software engineering tasks, emerging as a promising advancement to also enhance performance engineering practices. This talk reports challenges that we have afforded in integrating artificial intelligence techniques to support three essential activities in software performance engineering practice: code optimization, performance testing and continuous monitoring of software systems.