Augmenting, Not Replacing: The Role of LLMs in Human-Centric Formal RE: Supplemental Material

Authors

Sonora Halili, Smith College
Paola Spoletini, Kennesaw State University
Alicia M. Grubb, Smith CollegeFollow

Document Type

Article

Publication Date

2025

Publication Title

2025 33rd IEEE International Requirements Engineering Conference (RE'25)

Abstract

This repository contains the supplemental information for the RE'25 paper entitled "Augmenting, Not Replacing: The Role of LLMs in Human-Centric Formal RE" and the Smith College Departmental Honors Thesis entitled "The LTL Whisperer: Prompting AI to Explain Temporal Logic: Supplemental Information". This work investigates how and to what extent generative AI with large language models (LLMs) can assist practitioners and novices in interpreting formal requirements expressed in Linear Temporal Logic (LTL).

DOI

https://doi.org/10.35482/csc.004.2025

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Rights

@ the authors

Comments

Supplemental material: artifact-repo.zip (updated 6/11/25)

Additional files: README.pdf

Recommended Citation

Halili, Sonora; Spoletini, Paola; and Grubb, Alicia M., "Augmenting, Not Replacing: The Role of LLMs in Human-Centric Formal RE: Supplemental Material" (2025). Computer Science: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/csc_facpubs/407