CAIN 2024
Sun 14 - Mon 15 April 2024 Lisbon, Portugal
co-located with ICSE 2024

[Context] Applying design principles has long been acknowledged as beneficial for understanding and maintainability in traditional software projects. These benefits may similarly hold for Machine Learning (ML) projects, which involve iterative experimentation with data, models, and algorithms. However, ML components are often developed by data scientists with diverse educational backgrounds, potentially resulting in code that doesn’t adhere to software design best practices. [Goal] In order to better understand this phenomenon, we investigated the impact of the SOLID design principles on ML code understanding. [Method] To this end, we conducted a controlled experiment with three independent trials (exact replications), overall involving 100 data scientists. We restructured ML code from a real industrial setting that did not use SOLID principles. Within each trial, one group was presented with the original ML code, while the other one was presented with ML code incorporating SOLID principles. Participants of both groups were asked to analyze the code and fill out a questionnaire that included both open-ended and closed-ended questions on their understanding. [Results] The study results provide statistically significant evidence that the adoption of the SOLID design principles can improve code understanding within the realm of ML projects. [Conclusion] We put forward that software engineering design principles should be spread within the data science community and considered for enhancing the maintainability of ML code.

Sun 14 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
Architecting, Designing, Managing, and Modeling AI-Enabled SystemsIndustry Talks / Research and Experience Papers at Pequeno Auditório
Chair(s): Nicolás Cardozo Universidad de los Andes
11:00
10m
Talk
A Taxonomy of Foundation Model based Systems through the Lens of Software Architecture
Research and Experience Papers
Qinghua Lu Data61, CSIRO, Liming Zhu CSIRO’s Data61, Xiwei (Sherry) Xu Data61, CSIRO, Yue Liu CSIRO's Data61 & University of New South Wales, Zhenchang Xing CSIRO's Data61, Jon Whittle CSIRO's Data61 and Monash University
11:10
15m
Talk
Investigating the Impact of Solid Design Principles on Machine Learning Code UnderstandingDistinguished paper AwardDistinguished paper Award Candidate
Research and Experience Papers
Raphael Cabral Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Marcos Kalinowski Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Maria Teresa Baldassarre Department of Computer Science, University of Bari , Hugo Villamizar Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Tatiana Escovedo Pontifical Catholic University of Rio de Janeiro, Helio Côrtes Vieira Lopes PUC-Rio
Pre-print
11:25
10m
Industry talk
KnowING Intelligent Document Classification: A Deep Dive into Microservices and Efficient Models at ING
Industry Talks
A: Andrew Rutherfoord CWI; University of Groningen, A: Gert Vermeer , Andrea Capiluppi Brunel University
11:35
15m
Talk
An Exploratory Study of V-Model in Building ML-Enabled Software: A Systems Engineering PerspectiveDistinguished paper Award Candidate
Research and Experience Papers
Jie JW Wu University of British Columbia (UBC)
Pre-print
11:50
10m
Industry talk
Engineering Challenges in Industrial AI
Industry Talks
12:00
10m
Talk
Approach for Argumenting Safety on Basis of an Operational Design Domain
Research and Experience Papers
Gereon Weiss Fraunhofer IKS, Marc Zeller Siemens AG, Hannes Schoenhaar Siemens Corporate Technology, Christian Drabek Fraunhofer Institute for Cognitive Systems IKS, Andreas Kreutz Fraunhofer Institute for Cognitive Systems IKS
12:10
15m
Talk
The Impact of Knowledge Distillation on the Performance and Energy Consumption of NLP Models
Research and Experience Papers
Ye Yuan Vrije Universiteit Amsterdam, Jiacheng Shi Vrije Universiteit Amsterdam, Zongyao Zhang Vrije Universiteit Amsterdam, Kaiwei Chen Vrije Universiteit Amsterdam, Eloise Zhang Vrije Universiteit Amsterdam, Vincenzo Stoico Vrije Universiteit Amsterdam, Ivano Malavolta Vrije Universiteit Amsterdam