{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T20:02:26Z","timestamp":1762113746300,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T00:00:00Z","timestamp":1743379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3,31]]},"DOI":"10.1145\/3672608.3707754","type":"proceedings-article","created":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T18:26:21Z","timestamp":1747247181000},"page":"1730-1737","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Quality trade-offs in ML-enabled systems: a multiple-case study"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3413-2451","authenticated-orcid":false,"given":"Vladislav","family":"Indykov","sequence":"first","affiliation":[{"name":"Chalmers | University of Gothenburg, Gothenburg, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5449-7900","authenticated-orcid":false,"given":"Rebekka","family":"Wohlrab","sequence":"additional","affiliation":[{"name":"Chalmers | University of Gothenburg, Gothenburg, Sweden"},{"name":"Carnegie Mellon University, Pittsburgh, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5969-3521","authenticated-orcid":false,"given":"Daniel","family":"Str\u00fcber","sequence":"additional","affiliation":[{"name":"Chalmers | University of Gothenburg, Gothenburg, Sweden"},{"name":"Radboud University, Nijmegen, Netherlands"}]}],"member":"320","published-online":{"date-parts":[[2025,5,14]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Software quality trade-offs: A systematic map. IST","author":"Barney Sebastian","year":"2012","unstructured":"Sebastian Barney, Kai Petersen, Mikael Svahnberg, Ayb\u00fcke Aurum, and Hamish Barney. 2012. Software quality trade-offs: A systematic map. IST (2012)."},{"key":"e_1_3_2_1_2_1","volume-title":"Predicting supply chain risks using machine learning: The trade-off between performance and interpretability. Future Generation Computer Systems","author":"Baryannis George","year":"2019","unstructured":"George Baryannis, Samir Dani, and Grigoris Antoniou. 2019. Predicting supply chain risks using machine learning: The trade-off between performance and interpretability. Future Generation Computer Systems (2019)."},{"unstructured":"Len Bass Paul Clements and Rick Kazman. 2003. Software architecture in practice.","key":"e_1_3_2_1_3_1"},{"doi-asserted-by":"crossref","unstructured":"Manoj Bhat Klym Shumaiev Uwe Hohenstein Andreas Biesdorf and Florian Matthes. 2020. The evolution of architectural decision making as a key focus area of software architecture research: A semi-systematic literature study. In ICSA.","key":"e_1_3_2_1_4_1","DOI":"10.1109\/ICSA47634.2020.00015"},{"unstructured":"Jan Bosch. 2000. Design and use of software architectures: adopting and evolving a product-line approach. Pearson Education.","key":"e_1_3_2_1_5_1"},{"volume-title":"Exploring the accuracy-energy trade-off in machine learning","author":"Brownlee Alexander EI","unstructured":"Alexander EI Brownlee, Jason Adair, Saemundur O Haraldsson, and John Jabbo. 2021. Exploring the accuracy-energy trade-off in machine learning. In IEEE GI.","key":"e_1_3_2_1_6_1"},{"volume-title":"Innovation in transcribing data: Meet otter. ai","author":"Corrente Melissa","unstructured":"Melissa Corrente and Ivy Bourgeault. 2022. Innovation in transcribing data: Meet otter. ai. SAGE Publications, Ltd.","key":"e_1_3_2_1_7_1"},{"volume-title":"AI as a Service: Serverless machine learning with AWS","author":"Elger Peter","unstructured":"Peter Elger and E\u00f3in Shanaghy. 2020. AI as a Service: Serverless machine learning with AWS. Manning Publications.","key":"e_1_3_2_1_8_1"},{"unstructured":"International Organization for Standardization. 2023. ISO\/IEC 25059:2023 Software engineering \u2014 Systems and software Quality Requirements and Evaluation (SQuaRE) \u2014 Quality model for AI systems. Technical Report. ISO.","key":"e_1_3_2_1_9_1"},{"doi-asserted-by":"crossref","unstructured":"Xavier Franch Silverio Mart\u00ednez-Fern\u00e1ndez Claudia P Ayala and Cristina G\u00f3mez. 2022. Architectural decisions in AI-based systems: An ontological view. In QUATIC.","key":"e_1_3_2_1_10_1","DOI":"10.1007\/978-3-031-14179-9_2"},{"doi-asserted-by":"crossref","unstructured":"Christian Gilbertson Miranda Mundt Joshua Teves Simone Toribio and Reed Milewicz. 2024. Towards Evidence-Based Software Quality Practices for Reproducibility: Practices and Aligned Software Qualities. In ACM-REP.","key":"e_1_3_2_1_11_1","DOI":"10.1145\/3641525.3663624"},{"unstructured":"S.E. Hove and B. Anda. 2005. Experiences from conducting semi-structured interviews in empirical software engineering research. In METRICS.","key":"e_1_3_2_1_12_1"},{"key":"e_1_3_2_1_13_1","volume-title":"Architectural Tactics to Achieve Quality Attributes of Machine-Learning-Enabled Systems: A Systematic Literature Review. Available at SSRN 4909520","author":"Indykov Vladislav","year":"2024","unstructured":"Vladislav Indykov, Daniel Str\u00fcber, and Rebekka Wohlrab. 2024. Architectural Tactics to Achieve Quality Attributes of Machine-Learning-Enabled Systems: A Systematic Literature Review. Available at SSRN 4909520 (2024)."},{"key":"e_1_3_2_1_14_1","volume-title":"Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine","author":"Khalid Nazish","year":"2023","unstructured":"Nazish Khalid, Adnan Qayyum, Muhammad Bilal, Ala Al-Fuqaha, and Junaid Qadir. 2023. Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine (2023)."},{"key":"e_1_3_2_1_15_1","volume-title":"Toward Effective AI Support for Developers: A survey of desires and concerns. Queue","author":"Khemka Mansi","year":"2024","unstructured":"Mansi Khemka and Brian Houck. 2024. Toward Effective AI Support for Developers: A survey of desires and concerns. Queue (2024)."},{"key":"e_1_3_2_1_16_1","volume-title":"Quality-driven architecture development using architectural tactics. JSS","author":"Kim Suntae","year":"2009","unstructured":"Suntae Kim, Dae-Kyoo Kim, Lunjin Lu, and Sooyong Park. 2009. Quality-driven architecture development using architectural tactics. JSS (2009)."},{"key":"e_1_3_2_1_17_1","volume-title":"Engineering problems in machine learning systems. ML","author":"Kuwajima Hiroshi","year":"2020","unstructured":"Hiroshi Kuwajima, Hirotoshi Yasuoka, and Toshihiro Nakae. 2020. Engineering problems in machine learning systems. ML (2020)."},{"key":"e_1_3_2_1_18_1","volume-title":"AI in the EU: Ethical Guidelines as a Governance Tool","author":"Larsson Stefan","year":"2021","unstructured":"Stefan Larsson. 2021. AI in the EU: Ethical Guidelines as a Governance Tool. The European Union and the technology shift (2021)."},{"doi-asserted-by":"crossref","unstructured":"Sasu M\u00e4kinen Henrik Skogstr\u00f6m Eero Laaksonen and Tommi Mikkonen. 2021. Who needs MLOps: What data scientists seek to accomplish and how can MLOps help?. In WAIN.","key":"e_1_3_2_1_19_1","DOI":"10.1109\/WAIN52551.2021.00024"},{"volume-title":"Fundamentals of Software Startups: Essential Engineering and Business Aspects","author":"Melegati Jorge","unstructured":"Jorge Melegati and Fabio Kon. 2020. Early-stage software startups: main challenges and possible answers. In Fundamentals of Software Startups: Essential Engineering and Business Aspects. Springer, 129\u2013143.","key":"e_1_3_2_1_20_1"},{"doi-asserted-by":"crossref","unstructured":"Henry Muccini and Karthik Vaidhyanathan. 2021. Software architecture for ML-based systems: What exists and what lies ahead. In WAIN.","key":"e_1_3_2_1_21_1","DOI":"10.1109\/WAIN52551.2021.00026"},{"key":"e_1_3_2_1_22_1","volume-title":"A safe motion planning and reliable control framework for autonomous vehicles. T-IV","author":"Pan Huihui","year":"2024","unstructured":"Huihui Pan, Mao Luo, Jue Wang, Tenglong Huang, and Weichao Sun. 2024. A safe motion planning and reliable control framework for autonomous vehicles. T-IV (2024)."},{"doi-asserted-by":"crossref","unstructured":"Romesh Ranawana and Asoka S Karunananda. 2021. An agile software development life cycle model for machine learning application development. In SLAAI-ICAI.","key":"e_1_3_2_1_23_1","DOI":"10.1109\/SLAAI-ICAI54477.2021.9664736"},{"unstructured":"Maria Saenz Elena Revilla and Cristina Sim\u00f3n. 2020. Designing AI systems with human-machine teams.","key":"e_1_3_2_1_24_1"},{"doi-asserted-by":"crossref","unstructured":"Peter Santhanam. 2020. Quality management of machine learning systems. In EDSMLS. 1\u201313.","key":"e_1_3_2_1_25_1","DOI":"10.1007\/978-3-030-62144-5_1"},{"doi-asserted-by":"crossref","unstructured":"Alex Serban and Joost Visser. 2022. Adapting software architectures to machine learning challenges. In SANER. 152\u2013163.","key":"e_1_3_2_1_26_1","DOI":"10.1109\/SANER53432.2022.00029"},{"key":"e_1_3_2_1_27_1","volume-title":"Folkesson","author":"Shan Lijun","year":"2019","unstructured":"Lijun Shan, Behrooz Sangchoolie, and Peter et al. Folkesson. 2019. A survey on the applicability of safety, security and privacy standards in developing dependable systems. In SAFECOMP."},{"key":"e_1_3_2_1_28_1","volume-title":"Construction of a quality model for machine learning systems. SQ","author":"Siebert Julien","year":"2022","unstructured":"Julien Siebert, Lisa Joeckel, Jens Heidrich, Adam Trendowicz, Koji Nakamichi, Kyoko Ohashi, Isao Namba, Rieko Yamamoto, and Mikio Aoyama. 2022. Construction of a quality model for machine learning systems. SQ (2022)."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_29_1","DOI":"10.1613\/jair.1.13283"},{"doi-asserted-by":"crossref","unstructured":"Max van Haastrecht Matthieu Brinkhuis and Marco Spruit. 2024. Federated Learning Analytics: Investigating the Privacy-Performance Trade-Off in Machine Learning for Educational Analytics. In AIED.","key":"e_1_3_2_1_30_1","DOI":"10.1007\/978-3-031-64299-9_5"},{"key":"e_1_3_2_1_31_1","volume-title":"The agile requirements refinery: Applying SCRUM principles to software product management. IST","author":"Vlaanderen Kevin","year":"2011","unstructured":"Kevin Vlaanderen, Slinger Jansen, Sjaak Brinkkemper, and Erik Jaspers. 2011. The agile requirements refinery: Applying SCRUM principles to software product management. IST (2011)."}],"event":{"sponsor":["SIGAPP ACM Special Interest Group on Applied Computing"],"acronym":"SAC '25","name":"SAC '25: 40th ACM\/SIGAPP Symposium on Applied Computing","location":"Catania International Airport Catania Italy"},"container-title":["Proceedings of the 40th ACM\/SIGAPP Symposium on Applied Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672608.3707754","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3672608.3707754","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:57:32Z","timestamp":1750298252000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672608.3707754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,31]]},"references-count":31,"alternative-id":["10.1145\/3672608.3707754","10.1145\/3672608"],"URL":"https:\/\/doi.org\/10.1145\/3672608.3707754","relation":{},"subject":[],"published":{"date-parts":[[2025,3,31]]},"assertion":[{"value":"2025-05-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}