CAIN 2025
Sun 27 - Mon 28 April 2025 Ottawa, Ontario, Canada
co-located with ICSE 2025
Mon 28 Apr 2025 15:10 - 15:20 at 208 - Quality Assurance for AI systems Chair(s): Eduardo Santana de Almeida

Deep learning (DL) systems present unique challenges in software engineering, especially concerning quality attributes like correctness and resource efficiency. While DL models achieve exceptional performance in specific tasks, engineering DL-based systems is still essential. The effort, cost, and potential diminishing returns of continual improvements must be carefully evaluated, as software engineers often face the critical decision of when to stop refining a system relative to its quality attributes. This experience paper explores the role of MLOps practices—such as monitoring and experiment tracking—in creating transparent and reproducible experimentation environments that enable teams to assess and justify the impact of design decisions on quality attributes. Furthermore, we report on experiences addressing the quality challenges by embedding domain knowledge into the design of a DL model and its integration within a larger system. The findings offer actionable insights into not only the benefits of domain knowledge and MLOps but also the strategic consideration of when to limit further optimizations in DL projects to maximize overall system quality and reliability

Mon 28 Apr

Displayed time zone: Eastern Time (US & Canada) change

14:00 - 15:30
Quality Assurance for AI systemsResearch and Experience Papers at 208
Chair(s): Eduardo Santana de Almeida Federal University of Bahia
14:00
10m
Talk
Towards a Domain-Specific Modeling Language for Streamlined Change Management in AI Systems Development
Research and Experience Papers
Razan Abualsaud IRIT, CNRS, Toulouse
14:10
15m
Talk
An AI-driven Requirements Engineering Framework Tailored for Evaluating AI-Based Software
Research and Experience Papers
Hamed Barzamini , Fatemeh Nazaritiji Northern Illinois University, Annalise Brockmann Northern Illinois University, Hasan Ferdowsi Northern Illinois university, Mona Rahimi Northern Illinois University
14:25
15m
Talk
MLScent: A tool for Anti-pattern detection in ML projects
Research and Experience Papers
Karthik Shivashankar University of Oslo, Antonio Martini University of Oslo
14:40
15m
Talk
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)Distinguished paper Award Candidate
Research and Experience Papers
Boyue Caroline Hu University of Toronto, Divya Gopinath KBR; NASA Ames, Ravi Mangal Colorado State University, Nina Narodytska VMware Research, Corina S. Păsăreanu Carnegie Mellon University, Susmit Jha SRI
14:55
15m
Talk
Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems
Research and Experience Papers
Rodrigo Ximenes Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Antonio Pedro Santos Alves Pontifical Catholic University of Rio de Janeiro, Tatiana Escovedo Pontifical Catholic University of Rio de Janeiro, Rodrigo Spinola Virginia Commonwealth University, Marcos Kalinowski Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
Pre-print
15:10
10m
Talk
Addressing Quality Challenges in Deep Learning: The Role of MLOps and Domain Knowledge
Research and Experience Papers
Santiago del Rey Universitat Politècnica De Catalunya - Barcelona Tech, Adrià Medina Universitat Politècnica de Barcelona - BarcelonaTech (UPC), Xavier Franch Universitat Politècnica de Catalunya, Silverio Martínez-Fernández UPC-BarcelonaTech
Pre-print
15:20
10m
Other
Discussion
Research and Experience Papers

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