Publication Type
Transcript
Version
publishedVersion
Publication Date
11-2024
Abstract
In recent years, important advances in Artificial Intelligence (AI), and, in particular, in Machine Learning (ML), including Deep Learning (DL) and Large Language Models (LLMs), have caused a substantial increase of submissions to all Software Engineering (SE) venues (conferences and journals) related to SE with and for AI. They are commonly referred to as AI for SE and SE for AI.
Keywords
Scoping, Software Technology, Machine Learning Models, Artificial Intelligence Techniques, Model Checking, Complex Software
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Areas of Excellence
Digital transformation
Publication
IEEE Transactions on Software Engineering
Volume
50
Issue
11
First Page
2709
Last Page
2711
ISSN
0098-5589
Identifier
10.1109/TSE.2024.3470368
Publisher
Institute of Electrical and Electronics Engineers
Citation
UCHITEL, Sebastián; CHECHIK, Marsha; DI PENTA, Massimiliano; ADAMS, Bram; AGUIRRE, Nazareno; BAVOTA, Gabriele; BIANCULLI, Domenico; BLINCOE, Kelly; CAVALCANTI, Ana; DITTRICH, Yvonne; FERRUCCI, Filomena; HODA, Rashina; HUANG, LiGuo; David LO; and et al..
Scoping software engineering for AI: The TSE perspective. (2024). IEEE Transactions on Software Engineering. 50, (11), 2709-2711.
Available at: https://ink.library.smu.edu.sg/sis_research/9884
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TSE.2024.3470368
