| 2024 | Continuous Quality Assurance and ML Pipelines under the AI Act. | Matthias Wagner |
| 2024 | An Exploratory Study of Dataset and Model Management in Open Source Machine Learning Applications. | Tajkia Rahman Toma, Cor-Paul Bezemer |
| 2024 | Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory. | Saeid Tizpaz-Niari, Sriram Sankaranarayanan |
| 2024 | Taxonomy of Generative AI Applications for Risk Assessment. | Hiroshi Tanaka, Masaru Ide, Jun Yajima, Sachiko Onodera, Kazuki Munakata, Nobukazu Yoshioka |
| 2024 | Prompt Smells: An Omen for Undesirable Generative AI Outputs. | Krishna Ronanki, Beatriz Cabrero-Daniel, Christian Berger |
| 2024 | Modeling Resilience of Collaborative AI Systems. | Diaeddin Rimawi, Antonio Liotta, Marco Todescato, Barbara Russo |
| 2024 | Software Design Decisions for Greener Machine Learning-based Systems. | Santiago del Rey |
| 2024 | Data Selection Driven by Item Difficulty: On Investigating Data Efficient Practice for Hyperparameter Search. | Gustavo Rodrigues dos Reis, Adrian Mos, Mario Cortes Cornax, Cyril Labb |
| 2024 | Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality. | Gilberto Recupito, Raimondo Rapacciuolo, Dario Di Nucci, Fabio Palomba |
| 2024 | LLMs for Test Input Generation for Semantic Applications. | Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Abdelrazek |
| 2024 | Optimizing Data Analytics Workflows through User-driven Experimentation. | Keerthiga Rajenthiram |
| 2024 | Automating Patch Set Generation from Code Reviews Using Large Language Models. | Md Tajmilur Rahman, Rahul Singh, Mir Yousuf Sultan |
| 2024 | Is Your Anomaly Detector Ready for Change? Adapting AIOps Solutions to the Real World. | Lorena Poenaru-Olaru, Natalia Karpova, Luis Cruz, Jan S. Rellermeyer, Arie van Deursen |
| 2024 | Can causality accelerate experimentation in software systems? | Andrei Paleyes, Han-Bo Li, Neil D. Lawrence |
| 2024 | DVC in Open Source ML-development: The Action and the Reaction. | Lorena Barreto Simedo Pacheco, Musfiqur Rahman, Fazle Rabbi, Pouya Fathollahzadeh, Ahmad Abdellatif, Emad Shihab, Tse-Hsun (Peter) Chen, Jinqiu Yang, Ying Zou |
| 2024 | Energy-Efficient Development of ML-Enabled Systems: A Data-Centric Approach. | Rafiullah Omar |
| 2024 | Custom Developer GPT for Ethical AI Solutions. | Lauren Olson |
| 2024 | Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models. | Ali Nouri, Beatriz Cabrero-Daniel, Fredrik Trner, Hkan Sivencrona, Christian Berger |
| 2024 | Novel Contract-based Runtime Explainability Framework for End-to-End Ensemble Machine Learning Serving. | Minh-Tri Nguyen, Hong Linh Truong, Tram Truong Huu |
| 2024 | (Why) Is My Prompt Getting Worse? Rethinking Regression Testing for Evolving LLM APIs. | Wanqin Ma, Chenyang Yang, Christian Kstner |
| 2024 | Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. | Ziyu Li, Donghwan Shin |
| 2024 | A Combinatorial Approach to Hyperparameter Optimization. | Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn |
| 2024 | Green Runner: A Tool for Efficient Deep Learning Component Selection. | Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz |
| 2024 | Threat Modeling of ML-intensive Systems: Research Proposal. | Felix Viktor Jedrzejewski |
| 2024 | Component-based Approach to Software Engineering of Machine Learning-enabled Systems. | Vladislav Indykov |