TY - GEN
T1 - Normative Requirements Operationalization with Large Language Models
AU - Feng, Nick
AU - Marsso, Lina
AU - Getir Yaman, Sinem
AU - Standen, Isobel
AU - Baatartogtokh, Yesugen
AU - Ayad, Reem
AU - De Mello, Victoria Oldemburgo
AU - Townsend, Beverley
AU - Bartels, Hanne
AU - Cavalcanti, Ana
AU - Calinescu, Radu
AU - Chechik, Marsha
N1 - © 2024 IEEE. This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.
PY - 2024/8/21
Y1 - 2024/8/21
N2 - Normative non-functional requirements specify con-straints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms. As these requirements are typically defined by non-technical system stakeholders with different expertise and priorities (ethicists, lawyers, social scientists, etc.), ensuring their well-formedness and consistency is very challenging. Recent research has tackled this challenge using a domain-specific language to specify normative requirements as rules whose consistency can then be analysed with formal methods. In this paper, we propose a complemen-tary approach that uses Large Language Models to extract semantic relationships between abstract representations of system capabilities. These relations, which are often assumed implicitly by non-technical stakeholders (e.g., based on common sense or domain knowledge), are then used to enrich the automated reasoning techniques for eliciting and analyzing the consistency of normative requirements. We show the effectiveness of our approach to normative requirements elicitation and operational-ization through a range of real-world case studies. An extended version of this paper, which includes appendices is available at https://arxiv.org/abs/2404.12335
AB - Normative non-functional requirements specify con-straints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms. As these requirements are typically defined by non-technical system stakeholders with different expertise and priorities (ethicists, lawyers, social scientists, etc.), ensuring their well-formedness and consistency is very challenging. Recent research has tackled this challenge using a domain-specific language to specify normative requirements as rules whose consistency can then be analysed with formal methods. In this paper, we propose a complemen-tary approach that uses Large Language Models to extract semantic relationships between abstract representations of system capabilities. These relations, which are often assumed implicitly by non-technical stakeholders (e.g., based on common sense or domain knowledge), are then used to enrich the automated reasoning techniques for eliciting and analyzing the consistency of normative requirements. We show the effectiveness of our approach to normative requirements elicitation and operational-ization through a range of real-world case studies. An extended version of this paper, which includes appendices is available at https://arxiv.org/abs/2404.12335
KW - Elicitation and Validation
KW - Large Language Model
KW - Requirement Engineering
UR - http://www.scopus.com/inward/record.url?scp=85202749254&partnerID=8YFLogxK
U2 - 10.1109/RE59067.2024.00022
DO - 10.1109/RE59067.2024.00022
M3 - Conference contribution
AN - SCOPUS:85202749254
T3 - Proceedings of the IEEE International Conference on Requirements Engineering
SP - 129
EP - 141
BT - Proceedings - 32nd IEEE International Requirements Engineering Conference, RE 2024
A2 - Liebel, Grischa
A2 - Hadar, Irit
A2 - Spoletini, Paola
PB - IEEE Computer Society
T2 - 32nd IEEE International Requirements Engineering Conference, RE 2024
Y2 - 24 June 2024 through 28 June 2024
ER -