2 citations · 2 across the 6 of their papers we have counts for
9 papers
TDD Governance for Multi-Agent Code Generation via Prompt Engineering
Tarlan Hasanli, Shahbaz Siddeeq, Bishwash Khanal +3
Large language models (LLMs) accelerate software development but often exhibit instability, non-determinism, and weak adherence to development discipline in unconstrained workflows…
Agentic Frameworks for Reasoning Tasks: An Empirical Study
Zeeshan Rasheed, Abdul Malik Sami, Muhammad Waseem +3
Recent advances in agentic frameworks have enabled AI agents to perform complex reasoning and decision-making. However, evidence comparing their reasoning performance, efficiency,…
LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review
Zeeshan Rasheeda, Muhammad Waseema, Kai-Kristian Kemella +2
Large Language Models (LLMs) have enabled multi-agent systems to perform autonomous code generation for complex tasks. Despite the recent growth in research and industrial applicat…
AI and Agile Software Development: A Research Roadmap from the XP2025 Workshop
Zheying Zhang, Tomas Herda, Victoria Pichler +20
This paper synthesizes the key findings from a full-day XP2025 workshop on "AI and Agile: From Frustration to Success", held in Brugg-Windisch, Switzerland. The workshop brought to…
Mapping Trustworthiness in Large Language Models: A Bibliometric Analysis Bridging Theory to Practice
José Siqueira de Cerqueira, Kai-Kristian Kemell, Rebekah Rousi +3
The rapid proliferation of Large Language Models (LLMs) has raised significant trustworthiness and ethical concerns. Despite the widespread adoption of LLMs across domains, there i…
The EU AI Act is a good start but falls short
Chalisa Veesommai Sillberg, Jose Siqueira De Cerqueira, Pekka Sillberg +2
The EU AI Act was created to ensure ethical and safe Artificial Intelligence (AI) development and deployment across the EU. This study aims to identify key challenges and strategie…