CAIN 2022
Mon 16 - Tue 17 May 2022
co-located with ICSE 2022

Keynotes

We are excited to announce the following two keynotes.

  • Saleema Amershi (Microsoft Research): Challenges in creating responsible and human-centered AI
  • Christopher Re (Stanford University): Software 2.0, Foundation Models, Data-Centric AI, and why I’m excited enough to tolerate these buzzwords.

Accepted contributions

We are excited to announce the list of accepted papers, industry talks, and posters.

Tentative Program

Pacific Time Eastern Time Central European Beijing Time

May 16, 2022

3:00 6:00 12:00 18:00 Welcome to CAIN
Session 1 Quality Assurance
3:30 6:30 12:30 18:30 What is Software Quality for AI Engineers? Towards a Thinning of the Fog
Valentina Golendukhina, Valentina Lenarduzzi, Michael Felderer
3:45 6:45 12:45 18:45 Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
Qunying Song, Markus Borg, Emelie Engstrom, Håkan Ardö, Sergio Rico
4:00 7:00 13:00 19:00 Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
Markus Borg, Johan Bengtsson, Harald Österling, Alexander Hagelborn, Isabella Gagner, Piotr Tomaszewski
4:15 7:15 13:15 19:15 Discussion
4:30 7:30 13:30 19:30 Break
Session 2 Posters
4:45 7:45 13:45 19:45 Activity (TBD)
5:15 8:15 14:15 20:15 MLOps: Five Steps to Guide its Effective Implementation
Beatriz Matsui, Denise Goya
5:18 8:18 14:18 20:18 Towards A Methodological Framework for Production-ready AI-based Software Components
Markus Haug, Justus Bogner
5:21 8:21 14:21 20:21 Preliminary Insights to enable automation of the Software Development Process in Software StartUps. A Investigation Study from the use of Artificial Intelligence and Machine Learning
Olimar Borges, Valentina Lenarduzzi, Rafael Prikladnicki
5:24 8:24 14:24 20:24 Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise Adequacy
Mira Marhaba, Ettore Merlo, Foutse Khomh, Giuliano Antoniol
5:27 8:27 14:27 20:27 Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models
Yuejun GUo, Qiang Hu, Maxime Cordy, Mike Papadakis, Yves Le Traon
5:30 8:30 14:30 20:30 A New Approach for Machine Learning Security Risk Assessment
Jun Yajima, Maki Inui, Takanori Oikawa, Fumiyoshi Kasahara, Ikuya Morikawa, Nobukazu Yoshioka
5:33 8:33 14:33 20:33 TopSelect: A Topology-based Feature Selection Method for Industrial Machine Learning
Hadil Abukwaik, Lefter Sula, Pablo Rodriguez
5:36 8:36 14:36 20:36 Pynblint: a Static Analyzer for Python Jupyter Notebooks
Luigi Quaranta, Fabio Calefato, Filippo Lanubile
5:39 8:39 14:39 20:39 Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Jati Hiliamsyah Husen, Hironori Washizaki, Hnin Tun, Nobukazu Yoshioka, Hironori Takeuchi, Yoshiaki Fukazawa
5:42 8:42 14:42 20:42 Structural Causal Models as Boundary Objects in AI System Development
Hans-Martin Heyn, Eric Knauss
5:45 8:45 14:45 20:45 Poster Visits
6:15 9:15 15:15 21:15 Break
Session 3 Training & Learning
6:30 9:30 15:30 21:30 An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
6:45 9:45 15:45 21:45 Automatic Checkpointing and Deterministic Training for Deep Learning
Xiangzhe Xu, Hongyu Liu, Guanhong Tao, Zhou Xuan, Xiangyu Zhang
7:00 10:00 16:00 22:00 Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers
Adriano Franci, Maxime Cordy, Martin Gubri, Mike Papadakis, Yves Le Traon
7:15 10:15 16:15 22:15 Engineering a Platform for Reinforcement Learning Workloads [Industry Talk]
Ali Kanso, Kinshuman Patra
7:30 10:30 16:30 22:30 Method Cards for Prescriptive Machine-Learning Transparency
David Adkins, Bilal Alsallakh, Adeel Cheema, Narine Kokhlikyan, Emily McReynolds, Pushkar Mishra, Chavez Procope, Jeremy Sawruk, Erin Wang, Polina Zvyagina
7:45 10:45 16:45 22:45 Discussion
8:00 11:00 17:00 23:00 Break
8:15 11:15 17:15 23:15 Session 4 Keynote Christopher Re:
Software 2.0, Foundation Models, Data-Centric AI, and why I’m excited enough to tolerate these buzzwords.
9:15 12:15 18:15 0:15 (+1) End of Day 1

May 17, 2022

Session 5 AI Engineering Practices
3:00 6:00 12:00 18:00 Towards a Roadmap for Software Engineering for Responsible AI
Qinghua Lu, Liming Zhu, Xiwei Xu, Jon Whittle, Zhenchang Xing
3:15 6:15 12:15 18:15 AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering
Samuli Laato, Teemu Birkstedt, Matti Mäntymäki, Matti Minkkinen, Tommi Mikkonen
3:30 6:30 12:30 18:30 The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects
Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson
3:45 6:45 12:45 18:45 What Is an AI Engineer? An Empirical Analysis of Job Ads in the Netherlands
Marcel Meesters, Petra Heck, Alexander Serebrenik
4:00 7:00 13:00 19:00 Data is about Detail: An Empirical Investigation for Software Systems with NLP at Core
Anmol Singhal, Preethu Rose Anish, Pratik Sonar, Smita Ghaisas
4:15 7:15 13:15 19:15 Discussion
4:30 7:30 13:30 19:30 Break
Session 6 AI Models & Pipelines
4:45 7:45 13:45 19:45 Practical Insights of Repairing Model Problems on Image Classification [Industry Talk]
Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa
5:00 8:00 14:00 20:00 UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing
Erik Johannes Husom, Simeon Tverdal, Arda Goknil, Sagar Sen
5:15 8:15 14:15 20:15 Black-Box Models for Non-Functional Properties of AI Software Systems
Daniel Friesel, Olaf Spinczyk
5:30 8:30 14:30 20:30 Improving Generalizability of ML-enabled Software through Domain Specification
Hamed Barzamini, Mona Rahimi, Murtuza Shahzad, Hamed Alhoori
5:45 8:45 14:45 20:45 Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Marcel Altendeitering, Julia Pampus, Felix Larrinaga, Jon Legaristi, Falk Howar
6:00 9:00 15:00 21:00 Discussion
6:15 9:15 15:15 21:15 Break
Session 7 Smells
6:30 9:30 15:30 21:30 Activity (TBD)
7:00 10:00 16:00 22:00 Code Smells for Machine Learning Applications
Haiyin Zhang, Luís Cruz, Arie van Deursen
7:15 10:15 16:15 22:15 Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems
Harald Foidl, Michael Felderer, Rudolf Ramler
7:30 10:30 16:30 22:30 Data Smells in Public Datasets
Arumoy Shome, Luís Cruz, Arie van Deursen
7:45 10:45 16:45 22:45 Discussion
8:00 11:00 17:00 23:00 Break
8:15 11:15 17:15 23:15 Session 8 Keynote Saleema Amershi:
Challenges in creating responsible and human-centered AI
9:15 12:15 18:15 0:15 (+1) Closing and Awards
9:30 12:30 18:30 0:30 (+1) End of Day 2