10 papers
BT-APE: A Computationally Light Backtracking Approach to Automatic Prompt Engineering for Requirements Classification
Mohammad Amin Zadenoori, Waad Alhoshan, Jacek DÄ browski +2
Large language models (LLMs) are increasingly applied to requirements engineering (RE) tasks, yet the prompts guiding them are typically designed manually through trial and error,…
Class Model Generation from Requirements using Large Language Models
Jackson Nguyen, Rui En Koe, Fanyu Wang +2
The emergence of Large Language Models (LLMs) has opened new opportunities to automate software engineering activities that traditionally require substantial manual effort. Among t…
Software Self-Extension with SelfEvolve: an Agentic Architecture for Runtime Code Generation
Md Asif Iqbal Fahim, Oluwadamilola Adebayo, Alessio Ferrari
Traditional self-adaptive systems automatically reconfigure existing components in response to changing requirements, but provide limited support for the generation of novel functi…
RITA: A Tool for Automated Requirements Classification and Specification from Online User Feedback
Manjeshwar Aniruddh Mallya, Alessio Ferrari, Mohammad Amin Zadenoori +1
Context and motivation. Online user feedback is a valuable resource for requirements engineering, but its volume and noise make analysis difficult. Existing tools support individua…
From Online User Feedback to Requirements: Evaluating Large Language Models for Classification and Specification Tasks
Manjeshwar Aniruddh Mallya, Alessio Ferrari, Mohammad Amin Zadenoori +1
[Context and Motivation] Online user feedback provides valuable information to support requirements engineering (RE). However, analyzing online user feedback is challenging due to…
Does Model Size Matter? A Comparison of Small and Large Language Models for Requirements Classification
Mohammad Amin Zadenoori, Vincenzo De Martino, Jacek Dabrowski +2
[Context and motivation] Large language models (LLMs) show notable results in natural language processing (NLP) tasks for requirements engineering (RE). However, their use is compr…