Dr Nelly Bencomo nelly.bencomo@durham.ac.uk
Associate Professor
Dr Nelly Bencomo nelly.bencomo@durham.ac.uk
Associate Professor
Jin Guo
Rachel Harrison
Hans-Martin Heyn
Tim Menzies
Much has been written about the algorithmic role that AI plays for automation in SE. But what about the role of AI, augmented by human knowledge? Can we make a profound advance by combining human and artificial intelligence? Researchers in requirements engineering think so, arguing that requirement engineering is the secret weapon for better AI and better software.
Bencomo, N., Guo, J., Harrison, R., Heyn, H.-M., & Menzies, T. (2022). The Secret to Better AI and Better Software (Is Requirements Engineering). IEEE Software, 39(1), 105-110. https://doi.org/10.1109/ms.2021.3118099
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 14, 2021 |
Online Publication Date | Dec 23, 2021 |
Publication Date | 2022-02 |
Deposit Date | Jan 14, 2022 |
Publicly Available Date | Jan 17, 2022 |
Journal | IEEE Software |
Print ISSN | 0740-7459 |
Electronic ISSN | 1937-4194 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 39 |
Issue | 1 |
Pages | 105-110 |
DOI | https://doi.org/10.1109/ms.2021.3118099 |
Public URL | https://durham-repository.worktribe.com/output/1219885 |
Accepted Journal Article
(136 Kb)
PDF
Copyright Statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The role of models@run.time in supporting on-the-fly interoperability
(2012)
Journal Article
Reward-Reinforced Reinforcement Learning for Multi-agent Systems
(2021)
Journal Article
Perpetual Assurances for Self-Adaptive Systems
(2019)
Journal Article
The Uncertainty Interaction Problem in Self-Adaptive Systems
(2022)
Journal Article
Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning
(2021)
Journal Article
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search