Cover Image

A Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Taibi, Davide, Muccini, Henry, Vaidhyanathan, Karthik, Kalinowski, Marcos, Albano, Michele, Alves, Antonio Pedro Santos, Cerqueira, Renato, Devino, Mateus, Esposito, Matteo, Falcão, Rodrigo, Henning, Vinicius, Khomh, Foutse, Lenarduzzi, Valentina, Lu, Qinghua, Martínez, Matías, Mello, Henrique, Mendez, Daniel, Romao, Lucas
Format:	Preprint
Published:	2026
Subjects:	Software Engineering Artificial Intelligence Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative AI for Software Architecture. Applications, Challenges, and Future Directions
by: Esposito, Matteo, et al.
Published: (2025)

Can AI Agents Generate Microservices? How Far are We?
by: Adnan, Bassam, et al.
Published: (2026)

Microservice Generation
by: Bassam Adnan, et al.
Published: (2025)

Centrality Change Proneness: an Early Indicator of Microservice Architectural Degradation
by: Bakhtin, Alexander, et al.
Published: (2025)

Generative AI in Evidence-Based Software Engineering: A White Paper
by: Esposito, Matteo, et al.
Published: (2024)

Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis
by: Esposito, Matteo, et al.
Published: (2024)

Leveraging Network Methods for Hub-like Microservice Detection
by: Bakhtin, Alexander, et al.
Published: (2025)

On Large Language Models in Mission-Critical IT Governance: Are We Ready Yet?
by: Esposito, Matteo, et al.
Published: (2024)

Network Centrality as a New Perspective on Microservice Architecture
by: Bakhtin, Alexander, et al.
Published: (2025)

The Invisible Hand of AI Libraries Shaping Open Source Projects and Communities
by: Esposito, Matteo, et al.
Published: (2026)

SQuaD: The Software Quality Dataset
by: Robredo, Mikel, et al.
Published: (2025)

Evaluating Large Language Models for Detecting Architectural Decision Violations
by: Su, Ruoyu, et al.
Published: (2026)

Architectural Degradation: Definition, Motivations, Measurement and Remediation Approaches
by: Ahmad, Noman, et al.
Published: (2025)

Emerging Trends in Software Architecture from the Practitioners Perspective: A Five Year Review
by: Su, Ruoyu, et al.
Published: (2025)

Evaluating Time-Dependent Methods and Seasonal Effects in Code Technical Debt Prediction
by: Robredo, Mikel, et al.
Published: (2024)

Toward architecting self-coding information systems
by: Falcão, Rodrigo, et al.
Published: (2026)

Representation Improvement in Latent Space for Search-Based Testing of Autonomous Robotic Systems
by: Humeniuk, Dmytro, et al.
Published: (2025)

Autonomic Microservice Management via Agentic AI and MAPE-K Integration
by: Esposito, Matteo, et al.
Published: (2025)

Initial Insights on MLOps: Perception and Adoption by Practitioners
by: Moreschi, Sergio, et al.
Published: (2024)

Machine Learning Robustness: A Primer
by: Braiek, Houssem Ben, et al.
Published: (2024)

Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)
by: Pham, Phuoc, et al.
Published: (2025)

CppSATD: A Reusable Self-Admitted Technical Debt Dataset in C++
by: Sridharan, Murali, et al.
Published: (2025)

The Dual-Edged Sword of Technical Debt: Benefits and Issues Analyzed Through Developer Discussions
by: Li, Xiaozhou, et al.
Published: (2024)

Sovereign-by-Design A Reference Architecture for AI and Blockchain Enabled Systems
by: Esposito, Matteo, et al.
Published: (2026)

Early Career Developers' Perceptions of Code Understandability. A Study of Complexity Metrics
by: Esposito, Matteo, et al.
Published: (2023)

Making Sense of AI Agents Hype: Adoption, Architectures, and Takeaways from Practitioners
by: Su, Ruoyu, et al.
Published: (2026)

Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
by: Majdinasab, Vahid, et al.
Published: (2024)

On the Effectiveness of Log Representation for Log-based Anomaly Detection
by: Wu, Xingfang, et al.
Published: (2023)

GIST: Generated Inputs Sets Transferability in Deep Learning
by: Tambon, Florian, et al.
Published: (2023)

DeepCodeProbe: Towards Understanding What Models Trained on Code Learn
by: Majdinasab, Vahid, et al.
Published: (2024)

Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing
by: Humeniuk, Dmytro, et al.
Published: (2023)

Evaluating and Enhancing Segmentation Model Robustness with Metamorphic Testing
by: Mzoughi, Seif, et al.
Published: (2025)

Prism: Dynamic and Flexible Benchmarking of LLMs Code Generation with Monte Carlo Tree Search
by: Majdinasab, Vahid, et al.
Published: (2025)

Protecting Privacy in Software Logs: What Should Be Anonymized?
by: Aghili, Roozbeh, et al.
Published: (2024)

What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach
by: Wu, Xingfang, et al.
Published: (2024)

PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4
by: Abukhalaf, Seif, et al.
Published: (2024)

RefAgent: A Multi-agent LLM-based Framework for Automatic Software Refactoring
by: Oueslati, Khouloud, et al.
Published: (2025)

Toward Organizational Decoupling in Microservices Through Key Developer Allocation
by: Li, Xiaozhou, et al.
Published: (2025)

On the correlation between Architectural Smells and Static Analysis Warnings
by: Esposito, Matteo, et al.
Published: (2024)

LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges
by: Da Silva, Leuson, et al.
Published: (2024)