The School of Computer Science at the University of Windsor is pleased to present…
Knowledge Units of Programming Languages – A Novel Perspective for Leveraging Source Code to Support Software Engineering Tasks
Colloquium Presentation by: Dr. Md Ahasanuzzaman
Date: Friday, February 27
Time: 10:00 am - 11:00 AM
Location: Erie Hall, Room 3123
Abstract:
Traditional code metrics (e.g., LOC and cyclomatic complexity) do not reveal system traits that are tied to certain building blocks of a given programming language. Taking these building blocks of a programming language into account when studying software systems can lead to further insights about software systems. In this vein, we introduce Knowledge Units (KUs) of programming languages, a novel perspective of the source code to study software systems. We define KU as a cohesive set of key capabilities that are offered by one or more building blocks of a given programming language. We conceptualize and operationalize KUs and present a framework demonstrating how our KUs can be applied to study source code of software systems and support various software engineering tasks: (i) classifying post-release defects, (ii) recommending code reviewers in pull requests, (iii) predicting long-time contributors in open-source projects, and (iv) evaluating the capabilities of Foundation Models and Large Language Models (FM/LLMs) for code generation tasks. Our detailed empirical results show that KUs offer a new lens to study software systems and are effective in supporting software engineering tasks.
Biography:
Dr. Ahasanuzzaman completed his PhD from the School of Computing at Queen’s University, where he conducted research on software engineering and large-scale data analytics and AI in the SAIL Lab under the supervision of Prof. Ahmed E. Hassan. His research focuses on uncovering novel insights and innovative solutions to critically challenged and widely recognized problems in software engineering. By integrating AI techniques, natural language processing (NLP), and rigorous empirical analysis of large-scale data and mining software repositories, he aims to address key problems in developer engagement, software quality assurance, issue management, the mobile app ecosystem and the evaluation of Large Language Models (LLMs). He has published 12 peer-reviewed papers in top-tier venues such as TSE, EMSE, MSR and SANER. In recognition of his research excellence and academic achievements, he has received several prestigious awards, including the NSERC Canada Postdoctoral Research Award (CPRA), the Duncan and Urlla Carmichael Fellowship, and the Queen’s Graduate Research Fellowship. To learn more about his research, please visit https://ahsan2010.github.io/
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