3 citations · 3 across the 3 of their papers we have counts for
7 papers
Reporting LLM Prompting in Automated Software Engineering: A Guideline Based on Current Practices and Expectations
Alexander Korn, Lea Zaruchas, Chetan Arora +4
Large Language Models, particularly decoder-only generative models such as GPT, are increasingly used to automate Software Engineering tasks. These models are primarily guided thro…
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
Fanyu Wang, Chetan Arora, Yonghui Liu +5
Acceptance criteria (ACs) play a critical role in software development by clearly defining the conditions under which a software feature satisfies stakeholder expectations. However…
From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry
Chetan Arora, Fanyu Wang, Chakkrit Tantithamthavorn +2
Requirements engineering (RE) in the space industry is inherently complex, demanding high precision, alignment with rigorous standards, and adaptability to mission-specific constra…
Prompt Engineering for Requirements Engineering: A Literature Review and Roadmap
Kaicheng Huang, Fanyu Wang, Yutan Huang +1
Advancements in large language models (LLMs) have led to a surge of prompt engineering (PE) techniques that can enhance various requirements engineering (RE) tasks. However, curren…
AxBERT: An Interpretable Chinese Spelling Correction Method Driven by Associative Knowledge Network
Fanyu Wang, Hangyu Zhu, Zhenping Xie
Deep learning has shown promising performance on various machine learning tasks. Nevertheless, the uninterpretability of deep learning models severely restricts the usage domains t…
Requirements-Driven Automated Software Testing: A Systematic Review
Fanyu Wang, Chetan Arora, Chakkrit Tantithamthavorn +2
Automated software testing has significant potential to enhance efficiency and reliability within software development processes. However, its broader adoption faces considerable c…