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Code Automation Unleashed:
A Journey Into Transformative AI for Software Engineering
Speaker (s):
Antonio MASTROPAOLO
PhD Candidate
Software Engineering
Università della Svizzera italiana
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Date:
Time:
Venue:
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28 December 2023, Thursday
10:00am – 11:15am
School of Computing & Information
Systems 1 (SCIS 1),
Level 4, Meeting Room 4.4
Singapore Management University,
80 Stamford Road, Singapore 178902
We look forward to seeing you at this seminar.
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About the Talk
In recent years, the application of Artificial Intelligence (AI) to software engineering tasks has been changing how software is developed and maintained. In this seminar, the speaker will explain how AI, and in particular deep learning (DL) models, can streamline complex code-related tasks like those requiring the manipulation of multimodal data, such as code and technical natural language (e.g., automatically documenting a piece of code in natural language).
The speaker will review crucial technical aspects, including the importance of the pre-training phase that has led to unprecedented automation for specific code-related tasks. He will also present AI-based recommender systems developed in the context of his PhD, by discussing the main challenges faced during their design and empirical evaluation.
Finally, he will conclude the seminar by highlighting future directions for the field as an integral part of his medium-term research agenda.
About the Speaker
Antonio Mastropaolo is currently a Ph.D. candidate at the Università della Svizzera italiana (USI) in Switzerland, where he contributes to the Software Institute within the Faculty of Informatics. He started his Ph.D. in October 2020, after earning a Master of Science in Software System Security from Università degli Studi del Molise, Italy, in July 2020. Antonio's research focuses on software engineering, with a particular interest in automating code-related tasks such as bug-fixing and code summarization, to enhance the quality of software systems. His research exploits techniques which embrace natural language processing (NLP) and artificial intelligence (AI), with a strong focus on deep learning (DL) methods, to automate code-related tasks. Antonio's research has been featured in prominent software engineering forums, including the International Conference on Software Engineering (ICSE), International Conference on Automated Software Engineering (ASE), Transaction on Software Engineering (TSE), and Empirical Software Engineering (EMSE). Overall, at the present date, Antonio has published 13 works in top-tier software engineering venues, including 5 papers at ICSE, 1 at ASE, 2 at TSE, and 1 at EMSE.
He is a tenure-track faculty candidate for the Information Systems & Technology, Software Engineering cluster.
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