10 papers
Semantic-Enhanced Automatic Refinement of Architecture Recovery Results Using LLMs
Yiran Zhang, Chengwei Liu, Yuqiang Sun +5
Understanding the architecture is crucial for effectively maintaining and managing large software systems. However, discrepancies often exist between the designed and implemented a…
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…
Hallucination Detection for LLM-based Text-to-SQL Generation via Two-Stage Metamorphic Testing
Bo Yang, Yinfen Xia, Weisong Sun +1
In Text-to-SQL generation, large language models (LLMs) have shown strong generalization and adaptability. However, LLMs sometimes generate hallucinations, i.e.,unrealistic or illo…
UCRBench: Benchmarking LLMs on Use Case Recovery
Shuyuan Xiao, Yiran Zhang, Weisong Sun +3
Use cases are widely employed to specify functional requirements, yet existing benchmarks are scarce and face the risk of being misaligned with actual system behavior, similarly li…
Knowledge-Guided Multi-Agent Framework for Application-Level Software Code Generation
Qian Xiong, Bo Yang, Weisong Sun +4
Automated code generation driven by Large Lan- guage Models (LLMs) has enhanced development efficiency, yet generating complex application-level software code remains challenging.…
Requirements Development and Formalization for Reliable Code Generation: A Multi-Agent Vision
Xu Lu, Weisong Sun, Yiran Zhang +4
Automated code generation has long been considered the holy grail of software engineering. The emergence of Large Language Models (LLMs) has catalyzed a revolutionary breakthrough…