| 2023 | Maintaining and Monitoring AIOps Models Against Concept Drift. | Lorena Poenaru-Olaru, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen |
| 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 | Dataflow graphs as complete causal graphs. | Andrei Paleyes, Siyuan Guo, Bernhard Schlkopf, Neil D. Lawrence |
| 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 Kstner |
| 2023 | Enabling Machine Learning in Software Architecture Frameworks. | Armin Moin, Atta Badii, Stephan Gnnemann, Moharram Challenger |
| 2023 | AI Living Lab: Quality Assurance for AI-based Health systems. | Valentina Lenarduzzi, Minna Isomursu |
| 2023 | How Federated Machine Learning Helps Increase the Mutual Benefit of Data-Sharing Ecosystems. | Iva Krasteva, Boris Kraychev, Ensiye Kiyamousavi |
| 2023 | An Initial Analysis of Repair and Side-effect Prediction for Neural Networks. | Yuta Ishimoto, Ken Matsui, Masanari Kondo, Naoyasu Ubayashi, Yasutaka Kamei |
| 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 | 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 | 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 | Design Patterns for AI-based Systems: A Multivocal Literature Review and Pattern Repository. | Lukas Heiland, Marius Hauser, Justus Bogner |
| 2023 | Defining Quality Requirements for a Trustworthy AI Wildflower Monitoring Platform. | Petra Heck, Gerard Schouten |
| 2023 | A Case Study on AI Engineering Practices: Developing an Autonomous Stock Trading System. | Marcel Grote, Justus Bogner |
| 2023 | Conceptualising Software Development Lifecycle for Engineering AI Planning Systems. | Ilche Georgievski |
| 2023 | Reproducibility Requires Consolidated Artifacts. | Iordanis Fostiropoulos, Bowman Brown, Laurent Itti |
| 2023 | Engineering Challenges for AI-Supported Computer Vision in Small Uncrewed Aerial Systems. | Muhammed Tawfiq Chowdhury, Jane Cleland-Huang |
| 2023 | Towards Code Generation from BDD Test Case Specifications: A Vision. | Leon Chemnitz, David Reichenbach, Hani Aldebes, Mariam Naveed, Krishna Narasimhan, Mira Mezini |
| 2023 | Prevalence of Code Smells in Reinforcement Learning Projects. | Nicols Cardozo, Ivana Dusparic, Christian Cabrera |
| 2023 | Automatically Resolving Data Source Dependency Hell in Large Scale Data Science Projects. | Laurent Bou, Pratap Kunireddy, Pavle Subotic |
| 2022 | Code smells for machine learning applications. | Haiyin Zhang, Lus Cruz, Arie van Deursen |
| 2022 | Practical insights of repairing model problems on image classification. | Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa |
| 2022 | A new approach for machine learning security risk assessment: work in progress. | Jun Yajima, Maki Inui, Takanori Oikawa, Fumiyoshi Kasahara, Ikuya Morikawa, Nobukazu Yoshioka |
| 2022 | Checkpointing and deterministic training for deep learning. | Xiangzhe Xu, Hongyu Liu, Guanhong Tao, Zhou Xuan, Xiangyu Zhang |
| 2022 | Exploring ML testing in practice: lessons learned from an interactive rapid review with axis communications. | Qunying Song, Markus Borg, Emelie Engstrm, Hkan Ard, Sergio Rico |