Fuzzy Representation for Flexible Requirement Satisfaction

Ratih N.E. Anggraini; T. P. Martin

doi:10.1007/978-3-319-66939-7_3

Fuzzy Representation for Flexible Requirement Satisfaction

Ratih N.E. Anggraini^*, T. P. Martin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

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Abstract

The need for adaptive systems is growing with the increasing number of autonomous entities such as software systems and robots. A key characteristic of adaptive systems is that their environment changes, possibly in ways that were not envisaged at design-time. These changes in requirements, model and context mean the functional behaviour of a system cannot be fully defined in many cases, and consequently formal verification of the system is not possible. In this research, we propose a fuzzy representation to describe the result of requirement verification. We use an adaptive assisted living system as the case study. The RELAX language is used to create a flexible system specification. We model and simulate the system using UPPAAL 4 and use a fuzzy approach to translate the simulation result into fuzzy requirement satisfaction. The result shows the benefit of a more flexible representation by describing the degree of requirement satisfaction rather than a strict yes/no Boolean judgment.

Original language	English
Title of host publication	Advances in Computational Intelligence Systems -
Subtitle of host publication	Contributions Presented at the 17th UK Workshop on Computational Intelligence
Editors	Fei Chao , Steven Schockaert , Qingfu Zhang
Publisher	Springer
Pages	28-36
Number of pages	9
ISBN (Electronic)	9783319669397
ISBN (Print)	9783319669380
DOIs	https://doi.org/10.1007/978-3-319-66939-7_3
Publication status	Published - 5 Sept 2017
Event	17th UK Workshop on Computational Intelligence, UKCI 2017 - Cardiff, United Kingdom Duration: 6 Sept 2017 → 8 Sept 2017

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	650
ISSN (Print)	2194-5357

Conference

Conference	17th UK Workshop on Computational Intelligence, UKCI 2017
Country/Territory	United Kingdom
City	Cardiff
Period	6/09/17 → 8/09/17

Keywords

Adaptive system
Fuzzy
Requirement satisfaction

Access to Document

10.1007/978-3-319-66939-7_3

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Anggraini, R. N. E., & Martin, T. P. (2017). Fuzzy Representation for Flexible Requirement Satisfaction. In F. Chao , S. Schockaert , & Q. Zhang (Eds.), Advances in Computational Intelligence Systems - : Contributions Presented at the 17th UK Workshop on Computational Intelligence (pp. 28-36). (Advances in Intelligent Systems and Computing; Vol. 650). Springer. https://doi.org/10.1007/978-3-319-66939-7_3

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Anggraini, RNE & Martin, TP 2017, Fuzzy Representation for Flexible Requirement Satisfaction. in F Chao , S Schockaert & Q Zhang (eds), Advances in Computational Intelligence Systems - : Contributions Presented at the 17th UK Workshop on Computational Intelligence. Advances in Intelligent Systems and Computing, vol. 650, Springer, pp. 28-36, 17th UK Workshop on Computational Intelligence, UKCI 2017, Cardiff, United Kingdom, 6/09/17. https://doi.org/10.1007/978-3-319-66939-7_3

Fuzzy Representation for Flexible Requirement Satisfaction. / Anggraini, Ratih N.E.; Martin, T. P.
Advances in Computational Intelligence Systems - : Contributions Presented at the 17th UK Workshop on Computational Intelligence. ed. / Fei Chao ; Steven Schockaert ; Qingfu Zhang . Springer, 2017. p. 28-36 (Advances in Intelligent Systems and Computing; Vol. 650).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Anggraini, Ratih N.E.

AU - Martin, T. P.

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N2 - The need for adaptive systems is growing with the increasing number of autonomous entities such as software systems and robots. A key characteristic of adaptive systems is that their environment changes, possibly in ways that were not envisaged at design-time. These changes in requirements, model and context mean the functional behaviour of a system cannot be fully defined in many cases, and consequently formal verification of the system is not possible. In this research, we propose a fuzzy representation to describe the result of requirement verification. We use an adaptive assisted living system as the case study. The RELAX language is used to create a flexible system specification. We model and simulate the system using UPPAAL 4 and use a fuzzy approach to translate the simulation result into fuzzy requirement satisfaction. The result shows the benefit of a more flexible representation by describing the degree of requirement satisfaction rather than a strict yes/no Boolean judgment.

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Fuzzy Representation for Flexible Requirement Satisfaction

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