Abstract is missing.
- Linnaeus: A highly reusable and adaptable ML based log classification pipelineArmin Catovic, Carolyn Cartwright, Yasmin Tesfaldet Gebreyesus, Simone Ferlin. 11-18 [doi]
- Corner Case Data Description and DetectionTinghui Ouyang, Vicent Sanz Marco, Yoshinao Isobe, Hideki Asoh, Yutaka Oiwa, Yoshiki Seo. 19-26 [doi]
- Integration of Convolutional Neural Networks in Mobile ApplicationsRoger Creus Castanyer, Silverio Martínez-Fernández, Xavier Franch. 27-34 [doi]
- The Prevalence of Code Smells in Machine Learning projectsBart van Oort, Luis Cruz 0002, Maurício Aniche, Arie van Deursen. 35-42 [doi]
- Challenges and Governance Solutions for Data Science Services based on Open Data and APIsJuha-Pekka Joutsenlahti, Timo Lehtonen, Mikko Raatikainen, Elina Kettunen, Tommi Mikkonen. 43-46 [doi]
- Lessons Learned from Educating AI EngineersPetra Heck, Gerard Schouten. 47-50 [doi]
- Towards Risk Modeling for Collaborative AIMatteo Camilli, Michael Felderer, Andrea Giusti, Dominik T. Matt, Anna Perini, Barbara Russo, Angelo Susi. 51-54 [doi]
- Understanding and Modeling AI-Intensive System DevelopmentLuigi Lavazza, Sandro Morasca. 55-61 [doi]
- Robust Machine Learning in Critical Care - Software Engineering and Medical PerspectivesMiroslaw Staron, Helena Odenstedt Hergés, Silvana Naredi, Linda Block, Ali El-Merhi, Richard Vithal, Mikael Elam. 62-69 [doi]
- Systematic Mapping Study on the Machine Learning LifecycleYuanhao Xie, Luís Cruz, Petra Heck, Jan S. Rellermeyer. 70-73 [doi]
- Concepts in Testing of Autonomous Systems: Academic Literature and Industry PracticeQunying Song, Emelie Engström, Per Runeson. 74-81 [doi]
- MLOps Challenges in Multi-Organization Setup: Experiences from Two Real-World CasesTuomas Granlund, Aleksi Kopponen, Vlad Stirbu, Lalli Myllyaho, Tommi Mikkonen. 82-88 [doi]
- Requirement Engineering Challenges for AI-intense Systems DevelopmentHans-Martin Heyn, Eric Knauss, Amna Pir Muhammad, Olof Eriksson, Jennifer Linder, Padmini Subbiah, Shameer Kumar Pradhan, Sagar Tungal. 89-96 [doi]
- Practices for Engineering Trustworthy Machine Learning ApplicationsAlex Serban, Koen van der Blom, Holger H. Hoos, Joost Visser 0001. 97-100 [doi]
- Data acquisition and the implications of machine learning in the development of a Clinical Decision Support systemMilan Unger. 101-104 [doi]
- Data Collection and Utilization Framework for Edge AI ApplicationsHergys Rexha, Sébastien Lafond. 105-108 [doi]
- Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?Sasu Mäkinen, Henrik Skogström, Eero Laaksonen, Tommi Mikkonen. 109-112 [doi]
- Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics SystemsSophia J. Abraham, Zachariah Carmichael, Sreya Banerjee, Rosaura G. VidalMata, Ankit Agrawal, Md Nafee Al Islam, Walter J. Scheirer, Jane Cleland-Huang. 113-120 [doi]
- Software Architecture for ML-based Systems: What Exists and What Lies AheadHenry Muccini, Karthik Vaidhyanathan. 121-128 [doi]
- Towards Productizing AI/ML Models: An Industry Perspective from Data ScientistsFilippo Lanubile, Fabio Calefato, Luigi Quaranta, Maddalena Amoruso, Fabio Fumarola, Michele Filannino. 129-132 [doi]
- Characterizing and Detecting Mismatch in Machine-Learning-Enabled SystemsGrace A. Lewis, Stephany Bellomo, Ipek Ozkaya. 133-140 [doi]
- Engineering an Intelligent Essay Scoring and Feedback System: An Experience ReportAkriti Chadda, Kelly Song, Raman Chandrasekar, Ian Gorton. 141-144 [doi]