ICSME 2025
Sun 7 - Fri 12 September 2025 Auckland, New Zealand
Fri 12 Sep 2025 10:30 - 10:45 at Case Room 2 260-057 - Session 14 - Human Factors 2 Chair(s): Valeria Pontillo

Software testing ensures that a system functions correctly, meets specified requirements, and maintains high quality. As artificial intelligence (AI) and machine learning (ML) technologies become integral to software systems, testing has evolved to address their unique complexities. A critical advancement in this space is fairness testing, which identifies and mitigates biases in AI applications to promote ethical and equitable outcomes. Despite extensive academic research on fairness testing—including test input generation, test oracle identification, and component testing—practical adoption remains limited. Industry practitioners often lack clear guidelines and effective tools to integrate fairness testing into real-world AI development. This study investigates how software professionals test AI-powered systems for fairness through interviews with 25 practitioners working on AI and ML projects. Our findings highlight a significant gap between theoretical fairness concepts and industry practice. While fairness definitions continue to evolve, they remain difficult for practitioners to interpret and apply. The absence of industry-aligned fairness testing tools further complicates adoption, necessitating research into practical, accessible solutions. Key challenges include data quality and diversity, time constraints, defining effective metrics, and ensuring model interoperability. These insights emphasize the need to bridge academic advancements with actionable strategies and tools, enabling practitioners to systematically address fairness in AI systems.

Fri 12 Sep

Displayed time zone: Auckland, Wellington change

10:30 - 12:00
10:30
15m
Software Fairness Testing in Practice
Research Papers Track
10:45
15m
Refactoring Deep Learning Code: A Study of Practices and Unsatisfied Tool Needs
Research Papers Track
Siqi Wang Zhejiang University, Xing Hu Zhejiang University, Bei Wang Zhejiang University, China, Wenxin Yao Zhejiang University, Xin Xia Zhejiang University, Xinyu Wang Zhejiang University
11:00
10m
CodeWatcher: IDE Telemetry Data Extraction Tool for Understanding Coding Interactions with LLMs
Tool Demonstration Track
Manaal Ramadan Basha The University of British Columbia, Aimee M. Ribeiro Federal University of Para, Jeena Javahar The University of British Columbia, Gema Rodriguez-Perez The University of British Columbia, Cleidson de Souza Federal University of Pará, Brazil
11:10
15m
Understanding Practitioners’ Perspectives on Monitoring Machine Learning Systems
Industry Track
Hira Naveed Monash University, John Grundy Monash University, Chetan Arora Monash University, Hourieh Khalajzadeh Deakin University, Australia, Omar Haggag Monash University, Australia
Pre-print
11:25
15m
Using AI-based Coding Assistants in Practice: State of Affairs, Perceptions, and Ways Forward
Journal First Track
Agnia Sergeyuk JetBrains Research, Yaroslav Golubev JetBrains Research, Timofey Bryksin JetBrains Research, Iftekhar Ahmed University of California at Irvine
Link to publication DOI Pre-print
11:40
10m
An Empirical Study of GenAI Adoption in Open-Source Game Development: Tools, Tasks, and Developer Challenges
Registered Reports
Xiang Chen University of Waterloo, Wenhan Zhu Huawei Canada, Guoshuai Shi University of Waterloo, Michael W. Godfrey University of Waterloo, Canada
Pre-print
11:50
10m
Evaluating the Comprehension of the Stackage ecosystem: A Comparison Between VR and 2D Visualizations
Registered Reports
David Moreno-Lumbreras Universidad Rey Juan Carlos, Paul Leger Universidad Católica del Norte, Chile, Sergio Montes-León Universidad Rey Juan Carlos, Jesus M. Gonzalez-Barahona Universidad Rey Juan Carlos, Gregorio Robles Universidad Rey Juan Carlos