QuantUn: quantification of uncertainty for the reassessment of requirements

Nelly Bencomo

doi:10.1109/RE.2015.7320429

QuantUn: quantification of uncertainty for the reassessment of requirements

Nelly Bencomo^*

^*Corresponding author for this work

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.

Original language	English
Title of host publication	2015 IEEE 23rd International Requirements Engineering Conference (RE), proceedings
Publisher	IEEE
Pages	236-240
Number of pages	5
ISBN (Print)	978-1-4673-6905-3
DOIs	https://doi.org/10.1109/RE.2015.7320429
Publication status	Published - Nov 2015
Event	23rd IEEE International Requirements Engineering Conference - Ottawa, ON, Canada Duration: 24 Aug 2015 → 28 Aug 2015

Conference

Conference	23rd IEEE International Requirements Engineering Conference
Abbreviated title	RE 2015
Country/Territory	Canada
City	Ottawa, ON
Period	24/08/15 → 28/08/15

Keywords

Bayesian surprise
requirements assessment
requirements reflection
self-adaptation
uncertainty

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10.1109/RE.2015.7320429

Cite this

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title = "QuantUn: quantification of uncertainty for the reassessment of requirements",

abstract = "Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.",

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booktitle = "2015 IEEE 23rd International Requirements Engineering Conference (RE), proceedings",

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AB - Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.

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KW - requirements assessment

KW - requirements reflection

KW - self-adaptation

KW - uncertainty

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ER -

QuantUn: quantification of uncertainty for the reassessment of requirements

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Keywords

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