Scoping software engineering for AI: The TSE perspective

• Main Authors: 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, et al.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Scoping; Software Technology; Machine Learning Models; Artificial Intelligence Techniques; Model Checking; Complex Software; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/9884; https://ink.library.smu.edu.sg/context/sis_research/article/10884/viewcontent/Scoping_Software_Engineering_for_AI_The_TSE_Perspective.pdf
• Institution: Singapore Management University

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.