most citedSENAI: Towards Software Engineering Native Generative Artificial Intelligence

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2025

Hierarchical Evaluation of Software Design Capabilities of Large Language Models of Code

Mootez Saad, Boqi Chen, José Antonio Hernández López +2

Large language models (LLMs) are being increasingly adopted in the software engineering domain, yet the robustness of their grasp on core software design concepts remains unclear.…

cs.SE2025

MCeT: Behavioral Model Correctness Evaluation using Large Language Models

Khaled Ahmed, Jialing Song, Boqi Chen +2

Behavioral model diagrams, e.g., sequence diagrams, are an essential form of documentation that are typically designed by system engineers from requirements documentation, either f…

cs.AI2025

SHERPA: A Model-Driven Framework for Large Language Model Execution

Boqi Chen, Kua Chen, José Antonio Hernández López +3

Recently, large language models (LLMs) have achieved widespread application across various fields. Despite their impressive capabilities, LLMs suffer from a lack of structured reas…

cs.SE2025

Accurate and Consistent Graph Model Generation from Text with Large Language Models

Boqi Chen, Ou Wei, Bingzhou Zheng +1

Graph model generation from natural language description is an important task with many applications in software engineering. With the rise of large language models (LLMs), there i…

cs.SE2025

LLM-based Satisfiability Checking of String Requirements by Consistent Data and Checker Generation

Boqi Chen, Aren A. Babikian, Shuzhao Feng +2

Requirements over strings, commonly represented using natural language (NL), are particularly relevant for software systems due to their heavy reliance on string data manipulation.…

cs.SE20251 cited

SENAI: Towards Software Engineering Native Generative Artificial Intelligence

Mootez Saad, José Antonio Hernández López, Boqi Chen +3

Large Language Models have significantly advanced the field of code generation, demonstrating the ability to produce functionally correct code snippets. However, advancements in ge…