Understanding Software Engineering Artifacts with Large Language Models
Understanding Software Engineering Artifacts with Large Language Models
Software engineering relies on a diverse range of artifacts to support the analysis and decision-making process throughout the software development life cycle.
Large Language Models (LLMs) promise to transform how software engineers interact with these artifacts, but how capable are they in practice? This talk presents a series of empirical studies investigating the capabilities and limitations of LLMs across textual and visual software engineering artifacts.
The results reveal both impressive capabilities and important limitations, offering new insights into when LLMs can be trusted to support software engineering tasks and where human expertise remains indispensable.
Speaker
Associate Professor Sajjad Mahmood
A/Prof. Sajjad Mahmood is an associate professor of software engineering at the Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Saudi Arabia. He received his Ph.D. from La Trobe University, Melbourne, Australia, in May 2008. Before pursuing his Ph.D., he worked as a software engineer in the United States and Australia. He taught and designed several software engineering courses at KFUPM. He received the ‘Excellence in Teaching,’ Excellence in Instructional Technology, and ‘Excellence in Academic Advising’ awards from KFUPM. He is an active researcher in software engineering, having published over 120 articles in peer-reviewed journals and international conferences. He has organized software security engineering workshops co-located with the EASE conference for the last 6 years. His research interests include empirical software engineering, software security engineering, AI-based software engineering, and software process improvement in general.
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