LEGOS-SLEEC: Tool for Formalizing and Analyzing Normative Requirements

Systems interacting with humans, such as assistive robots or chatbots, are increasingly integrated into our society. To prevent these systems from causing social, legal, ethical, empathetic, or cultural (SLEEC) harms, normative requirements specify the permissible range of their behaviors. These req...

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Bibliographic Details
Published in:Proceedings (IEEE/ACM International Conference on Software Engineering Companion. Online) pp. 33 - 36
Main Authors: Kolyakov, Kevin, Marsso, Lina, Feng, Nick, Quan, Junwei, Chechik, Marsha
Format: Conference Proceeding
Language:English
Published: IEEE 27.04.2025
Subjects:
Debugging
Domain specific languages
DSL
Ethics
Law
Natural languages
Software engineering
Stakeholders
Uniform resource locators
User interfaces
ISSN:2574-1934
Online Access:Get full text
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Summary:Systems interacting with humans, such as assistive robots or chatbots, are increasingly integrated into our society. To prevent these systems from causing social, legal, ethical, empathetic, or cultural (SLEEC) harms, normative requirements specify the permissible range of their behaviors. These requirements encompass both functional and non-functional aspects and are defined with respect to time. Typically, these requirements are specified by stakeholders from a broad range of fields, such as lawyers, ethicists, or philosophers, who may lack technical expertise. Because such stakeholders often have different goals, responsibilities, and objectives, ensuring that these requirements are well-formed is crucial. SLEEC DSL, a domain-specific language resembling natural language, has been developed to formalize these requirements as SLEEC rules. In this paper, we present LEGOS-SLEEC, a tool designed to support interdisciplinary stakeholders in specifying normative requirements as SLEEC rules, and in analyzing and debugging their well-formedness. LEGOS-SLEEC is built using four previously published components, which have been shown to be effective and usable across nine case studies. Reflecting on this experience, we have significantly improved the user interface of LEGOS-SLEEC and its diagnostic support, and demonstrate the effectiveness of these improvements using four interdisciplinary stakeholders. Showcase video URL is https://youtu.be/LLaBLGxSi8A
ISSN:2574-1934
DOI:10.1109/ICSE-Companion66252.2025.00018