HM-Req: A Framework for Embedding Values within CPS Human Monitoring Requirements
Zoe Pfister, Ruth Breu, Michael Vierhauser
TLDR
HM-Req is a framework using a Controlled Natural Language to embed human values into CPS monitoring requirements, aiding conflict detection.
Key contributions
- Proposes HM-Req, a framework for eliciting human monitoring requirements in Cyber-Physical Systems.
- Introduces a Controlled Natural Language (CNL) to define requirements and augment them with human values.
- Integrates requirements and values into a Value Dashboard to detect potential conflicts.
- Validated the CNL's ability to capture diverse requirements and HM-Req's usefulness via surveys and interviews.
Why it matters
This paper addresses the critical gap of underrepresented human values in CPS requirements engineering. By systematically capturing and visualizing stakeholder values, HM-Req helps ensure ethical design and privacy in human-machine collaboration. It provides a structured approach to resolve value conflicts early in the design process.
Original Abstract
Monitoring humans, for example, their movement or location, is essential for safe and efficient human-machine collaboration in Cyber-Physical Systems (CPS). This information allows CPS to ensure safety properties, adapt their behaviour dynamically, and coordinate with humans. To ensure that the design of a CPS respects ethical principles and the privacy of its stakeholders, system requirements, particularly those related to human monitoring, must reflect the human values of all involved stakeholders. However, human values are often underrepresented in Software Engineering -- particularly during requirements elicitation and system design, crucial phases when introducing ethically critical functionality. Stakeholder values are often implicit and conflicting, yet rarely systematically captured. Furthermore, unstructured natural language requirements introduce ambiguity and vagueness, complicating conflict resolution. To address these problems, we propose HM-Req, a novel requirements elicitation framework including a Controlled Natural Language (CNL) for defining human monitoring requirements. These requirements are then augmented with human values from relevant stakeholders and integrated into a Value Dashboard to detect potential conflicts that require further discussion and resolution. Validation results, applying the CNL to different datasets and conducting a survey and expert interview, confirms the CNL's ability to capture diverse human monitoring requirements and show HM-Req's usefulness for requirements elicitation activities.
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