LLMs for Code: The Potential, Prospects, and Problems

Presenter: Tushar Sharma, Dalhousie University
Date: 12 June 2024


With the introduction of Large Language Models (LLMs) and their integration with software development tasks, the software development landscape has changed drastically in the last couple of years. In this session, we delve into the intricate world of large language models for code (LLM4Code) and explore their benefits, challenges, and threats. On one hand, these models have revolutionized code completion, bug detection, and even generated entire sections of code with remarkable accuracy. However, on the other side, several concerns have emerged surrounding inaccurate, buggy, and vulnerable code generation, biases, implications for climate, and the potential for unintended consequences. The talk promises an exploratory take that not only seeks to harness the potential of LLMs4Code but also ensures a conscientious and mindful approach toward their integration into our coding practices.


Tushar Sharma is a tenure-track assistant professor at Dalhousie University, Canada. He leads the Software Maintenance and Analytics Research Team (SMART) lab in the Faculty of Computer Science. Topics related to software engineering, sustainable artificial intelligence, and machine learning for software engineering (ML4SE) define his career interests. He earned a PhD from the Athens University of Economics and Business, Athens, Greece, specializing in software engineering in 2019. He has ten years of industry experience, mainly with Siemens Research, USA and India. He co-authored Refactoring for Software Design Smells: Managing Technical Debt and two Oracle Java certification books. He founded Designite, offering code quality assessment tools that many practitioners and researchers use worldwide. He is an IEEE Senior Member.