TY - JOUR
T1 - Explainable AI for SE
T2 - Challenges and future directions
AU - Tantithamthavorn, Chakkrit
AU - Cito, Jurgen
AU - Hemmati, Hadi
AU - Chandra, Satish
PY - 2023/5
Y1 - 2023/5
N2 - In recent years, artificial intelligence/machine learning (AI/ML) have been widely used in software engineering (SE) to improve developer productivity, software quality, and decision making. This includes well-known tools for code completion (for example, GitHub’s Copilot) but also code search; automated task recommendation; automated developer recommendation; automated defect/vulnerability/malware prediction, detection, localization, and repair; and many other purposes.
AB - In recent years, artificial intelligence/machine learning (AI/ML) have been widely used in software engineering (SE) to improve developer productivity, software quality, and decision making. This includes well-known tools for code completion (for example, GitHub’s Copilot) but also code search; automated task recommendation; automated developer recommendation; automated defect/vulnerability/malware prediction, detection, localization, and repair; and many other purposes.
UR - http://www.scopus.com/inward/record.url?scp=85156104914&partnerID=8YFLogxK
U2 - 10.1109/MS.2023.3246686
DO - 10.1109/MS.2023.3246686
M3 - Editorial
AN - SCOPUS:85156104914
SN - 0740-7459
VL - 40
SP - 29
EP - 33
JO - IEEE Software
JF - IEEE Software
IS - 3
ER -