| 2023 | 2nd IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2023, Melbourne, Australia, May 15-16, 2023 |
| 2023 | A Case Study on AI Engineering Practices: Developing an Autonomous Stock Trading System. Marcel Grote, Justus Bogner |
| 2023 | A Meta-Summary of Challenges in Building Products with ML Components - Collecting Experiences from 4758+ Practitioners. Nadia Nahar, Haoran Zhang, Grace A. Lewis, Shurui Zhou, Christian Kästner |
| 2023 | AI Living Lab: Quality Assurance for AI-based Health systems. Valentina Lenarduzzi, Minna Isomursu |
| 2023 | Algorithm Debt: Challenges and Future Paths. Emmanuel Iko-Ojo Simon, Melina C. Vidoni, Fatemeh H. Fard |
| 2023 | An Initial Analysis of Repair and Side-effect Prediction for Neural Networks. Yuta Ishimoto, Ken Matsui, Masanari Kondo, Naoyasu Ubayashi, Yasutaka Kamei |
| 2023 | Automatically Resolving Data Source Dependency Hell in Large Scale Data Science Projects. Laurent Boué, Pratap Kunireddy, Pavle Subotic |
| 2023 | Automotive Perception Software Development: An Empirical Investigation into Data, Annotation, and Ecosystem Challenges. Hans-Martin Heyn, Khan Mohammad Habibullah, Eric Knauss, Jennifer Horkoff, Markus Borg, Alessia Knauss, Polly Jing Li |
| 2023 | Conceptualising Software Development Lifecycle for Engineering AI Planning Systems. Ilche Georgievski |
| 2023 | Dataflow graphs as complete causal graphs. Andrei Paleyes, Siyuan Guo, Bernhard Schölkopf, Neil D. Lawrence |
| 2023 | Defining Quality Requirements for a Trustworthy AI Wildflower Monitoring Platform. Petra Heck, Gerard Schouten |
| 2023 | Design Patterns for AI-based Systems: A Multivocal Literature Review and Pattern Repository. Lukas Heiland, Marius Hauser, Justus Bogner |
| 2023 | Enabling Machine Learning in Software Architecture Frameworks. Armin Moin, Atta Badii, Stephan Günnemann, Moharram Challenger |
| 2023 | Engineering Challenges for AI-Supported Computer Vision in Small Uncrewed Aerial Systems. Muhammed Tawfiq Chowdhury, Jane Cleland-Huang |
| 2023 | Exploring Hyperparameter Usage and Tuning in Machine Learning Research. Sebastian Simon, Nikolay Kolyada, Christopher Akiki, Martin Potthast, Benno Stein, Norbert Siegmund |
| 2023 | Extensible Modeling Framework for Reliable Machine Learning System Analysis. Jati H. Husen, Hironori Washizaki, Hnin Thandar Tun, Nobukazu Yoshioka, Yoshiaki Fukazawa, Hironori Takeuchi, Hiroshi Tanaka, Kazuki Munakata |
| 2023 | How Federated Machine Learning Helps Increase the Mutual Benefit of Data-Sharing Ecosystems. Iva Krasteva, Boris Kraychev, Ensiye Kiyamousavi |
| 2023 | Maintaining and Monitoring AIOps Models Against Concept Drift. Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen |
| 2023 | Prevalence of Code Smells in Reinforcement Learning Projects. Nicolás Cardozo, Ivana Dusparic, Christian Cabrera |
| 2023 | Replay-Driven Continual Learning for the Industrial Internet of Things. Sagar Sen, Simon Myklebust Nielsen, Erik Johannes Husom, Arda Goknil, Simeon Tverdal, Leonardo Sastoque Pinilla |
| 2023 | Reproducibility Requires Consolidated Artifacts. Iordanis Fostiropoulos, Bowman Brown, Laurent Itti |
| 2023 | Tenet: A Flexible Framework for Machine-Learning-based Vulnerability Detection. Eduard Pinconschi, Sofia Reis, Chi Zhang, Rui Abreu, Hakan Erdogmus, Corina S. Pasareanu, Limin Jia |
| 2023 | Towards Code Generation from BDD Test Case Specifications: A Vision. Leon Chemnitz, David Reichenbach, Hani Aldebes, Mariam Naveed, Krishna Narasimhan, Mira Mezini |
| 2023 | Towards Concrete and Connected AI Risk Assessment (C Boming Xia, Qinghua Lu, Harsha Perera, Liming Zhu, Zhenchang Xing, Yue Liu, Jon Whittle |
| 2023 | Towards Understanding Machine Learning Testing in Practise. Arumoy Shome, Luís Cruz, Arie van Deursen |
| 2023 | Towards Understanding Model Quantization for Reliable Deep Neural Network Deployment. Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie, Wei Ma, Mike Papadakis, Yves Le Traon |
| 2023 | Trustworthy and Robust AI Deployment by Design: A framework to inject best practice support into AI deployment pipelines. András Schmelczer, Joost Visser |
| 2023 | Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI. Tim Yarally, Luis Cruz, Daniel Feitosa, June Sallou, Arie van Deursen |
| 2023 | safe.trAIn - Engineering and Assurance of a Driverless Regional Train. Marc Zeller, Martin Rothfelder, Cornel Klein |