CAIN 2026
Sun 12 - Sat 18 April 2026 Rio de Janeiro, Brazil
co-located with ICSE 2026
Sun 12 Apr 2026 11:00 - 11:08 at Oceania X - Engineering Agentic Systems Chair(s): Henry Muccini

The rise of foundation-model-based agents has introduced a new generation of intelligent systems capable of autonomous reasoning, reflection, and coordination. However, their specification remains challenging due to emergent behaviors and dynamic, probabilistic interactions that exceed the assumptions of traditional software and requirements engineering approaches. This short paper presents the vision of PerSpecAgents, a perspective-based approach designed to support the specification of intelligent systems involving such agents. The solution proposal extends an ML-enabled system specification approach by incorporating agent-oriented concerns, such as autonomy, reasoning loops, reflection mechanisms, memory management, and ethical guardrails. An initial academic validation with graduate-level participants allowed refinements and provided a preliminary indication of PerSpecAgents’ clarity, completeness, and usefulness. These findings strengthen our confidence in the approach’s potential to support the specification of intelligent systems built upon foundation models.

Sun 12 Apr

Displayed time zone: Brasilia, Distrito Federal, Brazil change

11:00 - 12:30
Engineering Agentic SystemsIndustry Track / Research Track / CAIN Program at Oceania X
Chair(s): Henry Muccini University of L'Aquila, Italy
11:00
8m
Short-paper
Towards an Approach for Specifying Intelligent Systems Involving Foundation Model Based AgentsShort Paper
Research Track
Júlia Condé Araújo Department of Informatics - Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Marina Condé Araújo Department of Informatics - Pontifical Catholic University of Rio de Janeiro (PUC-Rio), José M. C. Boaro Pontifical Catholic University of Rio de Janeiro, Marcos Kalinowski Pontifical Catholic University of Rio de Janeiro (PUC-Rio)
11:08
12m
Full-paper
Saving SWE-Bench: A Benchmark Mutation Approach for Realistic Agent EvaluationFull Paper
Research Track
Spandan Garg Microsoft Corporation, Benjamin Steenhoek Microsoft, Yufan Huang
Pre-print
11:20
12m
Industry talk
Context Sharing Strategies for Production Multi-Agent AI Systems: An Industrial EvaluationFull PaperVirtual Attendance
Industry Track
Minav Suresh Patel Independent Researcher, Rohit Dhawan Independent Researcher, Priyank Desai Amazon.com, Ankush Dhar Amazon
Media Attached
11:32
8m
Industry talk
Managing Variability in Industrial AI Agents for Manufacturing: Experiences at HitachiShort Paper
Industry Track
DOI
11:40
8m
Short-paper
Architecting AgentOps Needs CHANGEShort Paper
Research Track
Shaunak Biswas IIIT Hyderabad, Hiya Bhatt IIIT Hyderabad, Karthik Vaidhyanathan IIIT Hyderabad
Pre-print
11:48
12m
Industry talk
How to Build AI Agents by Augmenting LLMs with Codified Human Expert Domain Knowledge? A Software Engineering FrameworkFull Paper
Industry Track
Choro Ulan Uulu Eindhoven University of Technology, Mikhail Kulyabin , Iris Fuhrmann , Jan Joosten , Nuno Miguel Martins Pacheco , Filippos Petridis , Rebecca Johnson , Jan Bosch Chalmers University of Technology, Helena Holmström Olsson Malmö University
12:00
12m
Full-paper
Agentic AI Architecture for Evaluating and Improving Reinforcement Learning PipelinesFull Paper
Research Track
Evangelos Ntentos University of Vienna, Uwe Zdun University of Vienna
12:12
18m
Live Q&A
Joint Q&A (Engineering Agentic Systems)
CAIN Program