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Proceedings ArticleDOI

Towards modelling and reasoning support for early-phase requirements engineering

Eric Yu
- 05 Jan 1997 - 
- pp 226-235
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TLDR
This paper argues that a different kind of modelling and reasoning support is needed for the early phase of requirements engineering, which aims to model and analyze stakeholder interests and how they might be addressed, or compromised, by various system-and-environment alternatives.
Abstract
Requirements are usually understood as stating what a system is supposed to do, as apposed to how it should do it. However, understanding the organizational context and rationales (the "Whys") that lead up to systems requirements can be just as important for the ongoing success of the system. Requirements modelling techniques can be used to help deal with the knowledge and reasoning needed in this earlier phase of requirements engineering. However most existing requirements techniques are intended more for the later phase of requirements engineering, which focuses on completeness, consistency, and automated verification of requirements. In contrast, the early phase aims to model and analyze stakeholder interests and how they might be addressed, or compromised, by various system-and-environment alternatives. This paper argues, therefore, that a different kind of modelling and reasoning support is needed for the early phase. An outline of the i* framework is given as an example of a step in this direction. Meeting scheduling is used as a domain example.

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A Framework for Requirements Engineering Using System Dynamics

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TL;DR: A Requirements Engineering framework that is motivated by the System Dynamics paradigm is presented that consists of four key activities: ontology modelling, goal modelling, process modelling and scenarios generation and the premise that the synergy between these four activities results in a robust way of working.
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Goal-conflict likelihood assessment based on model counting

TL;DR: A novel automated approach to assess how likely a conflict is, that applies to general conflicts (not only obstacles) without requiring probabilistic information on the domain is presented.
References
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Book

The Sciences of the Artificial

TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
Book

Reengineering the corporation: a manifesto for business revolution

TL;DR: In this paper, the authors set aside much of the received wisdom of the last 200 years of industrial management and in its place presented a new set of organizing principles by which managers can rebuild their businesses.
Journal ArticleDOI

A field study of the software design process for large systems

TL;DR: A layered behavioral model is used to analyze how three of these problems—the thin spread of application domain knowledge, fluctuating and conflicting requirements, and communication bottlenecks and breakdowns—affected software productivity and quality through their impact on cognitive, social, and organizational processes.
Journal ArticleDOI

Goal-directed requirements acquisition

TL;DR: An approach to requirements acquisition is presented which is driven by higher-level concepts that are currently not supported by existing formal specification languages, such as goals to be achieved, agents to be assigned, alternatives to be negotiated, etc.
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