8 papers
Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability
Xianyou Li, Weiran Yan, Yichao Wu +4
Failure-aware observability diagnoses wasted computation in multi-agent LLM systems before final-answer evaluation can explain what went wrong. We propose a trace-based framework f…
Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory
Ruiyin Li, Yiran Zhang, Xiyu Zhou +6
Software architecture design is a critical yet inherently complex and knowledge-intensive phase that requires balancing competing quality attributes and adapting to evolving requir…
Unveiling the Role of ChatGPT in Software Development: Insights from Developer-ChatGPT Interactions on GitHub
Ruiyin Li, Peng Liang, Yifei Wang +3
The advent of Large Language Models (LLMs) has introduced a new paradigm in Software Engineering (SE), with generative AI tools like ChatGPT gaining widespread adoption among devel…
Using LLMs in Generating Design Rationale for Software Architecture Decisions
Xiyu Zhou, Ruiyin Li, Peng Liang +4
Design Rationale (DR) for software architecture decisions refers to the reasoning underlying architectural choices, which provides valuable insights into the different phases of th…
Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale
Yangxiao Cai, Ruiyin Li, Peng Liang +2
As the complexity of Software Engineering (SE) tasks continues to escalate, Multi-Agent Systems (MASs) have emerged as a focal point of research and practice due to their autonomy…
MAAD: Automate Software Architecture Design through Knowledge-Driven Multi-Agent Collaboration
Ruiyin Li, Yiran Zhang, Xiyu Zhou +5
Software architecture design is a critical, yet inherently complex and knowledge-intensive phase of software development. It requires deep domain expertise, development experience,…