A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

B. H. C. Cheng; Peter Sawyer; Nelly Bencomo; Jon Whittle

doi:10.1007/978-3-642-04425-0_36

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

B. H. C. Cheng, Peter Sawyer, Nelly Bencomo, Jon Whittle

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

Abstract

Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty.

Original language	English
Title of host publication	Model driven engineering languages and systems
Subtitle of host publication	12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings
Editors	Andy Schürr, Bran Selic
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	468-483
Number of pages	16
ISBN (Electronic)	978-3-642-04425-0
ISBN (Print)	978-3-642-04424-3
DOIs	https://doi.org/10.1007/978-3-642-04425-0_36
Publication status	Published - Oct 2009
Event	ACM/IEEE 12th international conference on model driven engineering languages and systems - Denver, CO, United States Duration: 4 Oct 2009 → 9 Oct 2009

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Number	5795
ISSN (Print)	0302-9743

Conference

Conference	ACM/IEEE 12th international conference on model driven engineering languages and systems
Abbreviated title	MoDELS 2009
Country/Territory	United States
City	Denver, CO
Period	4/10/09 → 9/10/09

Keywords

requirements engineering
goal models
uncertainty
dynamically adaptive systems

Access to Document

10.1007/978-3-642-04425-0_36

Cite this

Cheng, B. H. C., Sawyer, P., Bencomo, N., & Whittle, J. (2009). A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. In A. Schürr, & B. Selic (Eds.), Model driven engineering languages and systems: 12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings (pp. 468-483). (Lecture notes in computer science; No. 5795). Springer. https://doi.org/10.1007/978-3-642-04425-0_36

Cheng, B. H. C. ; Sawyer, Peter ; Bencomo, Nelly et al. / A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. Model driven engineering languages and systems: 12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings. editor / Andy Schürr ; Bran Selic. Berlin (DE) : Springer, 2009. pp. 468-483 (Lecture notes in computer science; 5795).

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abstract = "Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty.",

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Cheng, BHC, Sawyer, P, Bencomo, N & Whittle, J 2009, A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. in A Schürr & B Selic (eds), Model driven engineering languages and systems: 12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings. Lecture notes in computer science, no. 5795, Springer, Berlin (DE), pp. 468-483, ACM/IEEE 12th international conference on model driven engineering languages and systems, Denver, CO, United States, 4/10/09. https://doi.org/10.1007/978-3-642-04425-0_36

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. / Cheng, B. H. C.; Sawyer, Peter; Bencomo, Nelly et al.
Model driven engineering languages and systems: 12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings. ed. / Andy Schürr; Bran Selic. Berlin (DE): Springer, 2009. p. 468-483 (Lecture notes in computer science; No. 5795).

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

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Cheng BHC, Sawyer P, Bencomo N, Whittle J. A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. In Schürr A, Selic B, editors, Model driven engineering languages and systems: 12th international conference, MODELS 2009, Denver, CO, USA, October 4-9, 2009 : proceedings. Berlin (DE): Springer. 2009. p. 468-483. (Lecture notes in computer science; 5795). doi: 10.1007/978-3-642-04425-0_36

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

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