research-article

FORMS: a formal reference model for self-adaptation

Authors:

Jesper AnderssonAuthors Info & Claims

ICAC '10: Proceedings of the 7th international conference on Autonomic computing

Pages 205 - 214

https://doi.org/10.1145/1809049.1809078

Published: 07 June 2010 Publication History

Abstract

Self-adaptive software systems are an emerging class of systems that adjust their behavior at runtime to achieve certain functional or quality of service objectives. The construction of such systems has shown to be significantly more challenging than traditional systems, partly because researchers and practitioners have been struggling with the lack of a precise method of describing, comparing, and evaluating alternative architectural choices. In this paper, we introduce a reference model, entitled FOrmal Reference Model for Self-adaptation (FORMS), which intends to alleviate this pressing issue. FORMS consists of a small number of formally specified modeling primitives that correspond to the key variation points within self-adaptive software systems, and a set of relationships that guide their composition. We present our experiences with applying FORMS to several existing systems, which not only demonstrates its ability to precisely illuminate their underlying characteristics, but also its potential as a method of rigorously specifying architectural patterns for this domain.

References

[1]

J. Andersson et al. Modeling dimensions of self-adaptive software systems. In B. H. C. Cheng et al., editors, LNCS Hot Topics on Software Engineering for Self-Adaptive Systems. Springer, 2009.

Digital Library

[2]

J. Andersson et al. Reflecting on self-adaptive software systems. In Workshop on Software Engineering for Adaptive and Self-Managing Systems, Vancouver, BC, May 2009.

Digital Library

[3]

Y. Brun et al. Engineering self-adaptive systems through feedback loops. In Software Engineering for Self-Adaptive Systems. LNCS Hot Topics, 2009.

Digital Library

[4]

B. Cheng et al. Software engineering for self-adaptive systems: A research road map. In B. H. C. Cheng et al., editors, LNCS Hot Topics Software Engineering for Self-Adaptive Systems. Springer, 2009.

Digital Library

[5]

G. Coulson et al. A generic component model for building systems software. ACM Trans. Comput. Syst., 26(1), 2008.

Digital Library

[6]

CZT. http://czt.sourceforge.net/, Jan 2010.

[7]

S. Dobson et al. A survey of autonomic communications. TAAS, 1(2):223--259, 2006.

Digital Library

[8]

J. Dowling and V. Cahill. The k-Component architecture meta-model for self-adaptive software. In Int'l Conf. on Metalevel Architectures and Separation of Crosscutting Concerns, London, UK, 2001. Springer-Verlag.

Digital Library

[9]

G. Edwards et al. Architecture-driven self-adaptation and self-management in robotics systems. In Workshop on Software Engineering for Adaptive and Self-Managing Systems, Vancouver, BC, May 2009.

Digital Library

[10]

D. Garlan et al. Rainbow: Architecture-based self-adaptation with reusable infrastructure. IEEE Computer, Oct 2004.

Digital Library

[11]

M. C. Huebscher and J. A. McCann. A survey of autonomic computing - degrees, models, and applications. ACM Comput. Surv, 40(3), 2008.

Digital Library

[12]

J. O. Kephart and D. M. Chess. The vision of autonomic computing. Computer, 36(1):41--50, 2003.

Digital Library

[13]

J. Kramer and J. Magee. Self-managed systems: an architectural challenge. In Int'l Conf. on Software Engineering, May 2007.

Digital Library

[14]

P. Maes. Concepts and experiments in computational reflection. In OOPSLA, Orlando, FL, Oct 1987.

Digital Library

[15]

B. Miller. The autonomic computing edge: The role of knowledge in autonomic systems., Sep 2005.

[16]

P. Oreizy and others. Architecture-based runtime software evolution. In Int'l Conf. on Software engineering, Kyoto, Japan, May 1998.

Digital Library

[17]

G. Seetharaman et al. Unmanned vehicles come of age: The DARPA grand challenge. IEEE Computer, Dec. 2006.

Digital Library

[18]

M. Shaw. Beyond objects: A software design paradigm based on process control. ACM SIGSOFT Software Engineering Notes, 20(1):27--38, Jan. 1995.

Digital Library

[19]

M. Wermelinger and J. L. Fiadeiro. Algebraic software architecture reconfiguration. In European Software Engineering Conf. and Int'l Symp. on Foundations of Software Engineering, Toulouse, France, 1999 1999.

Digital Library

[20]

D. Weyns, S. Malek, and J. Andersson. Z specifications of FORMS. In CW 579, Tech. Report, Katholieke Universiteit Leuven, 2010. http://www.cs.kuleuven.be/publicaties/rapporten/cw/CW579.abs.html.

[21]

J. Zhang and B. H. C. Cheng. Model-based development of dynamically adaptive software. In International Conference on Software Engineering, Shanghai, China, May 2006.

Digital Library

Cited By

Affonso FNagassaki Campos GGuiguer Menaldo G(2024)A Reference Architecture Based on Reflection for Self-Adaptive Software: A Second ReleaseIEEE Access10.1109/ACCESS.2024.342836812(97476-97499)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3428368
Weyns DBäck TVidal RYao XBelbachir A(2023)The vision of self-evolving computing systemsJournal of Integrated Design and Process Science10.3233/JID-22000326:3-4(351-367)Online publication date: 13-Oct-2023
https://doi.org/10.3233/JID-220003
Provoost MWeyns DVan Landuyt DMichiels SBureš T(2023)Joint Learning: A Pattern for Reliable and Efficient Decision-Making in Self-Adaptive Internet of ThingsProceedings of the 28th European Conference on Pattern Languages of Programs10.1145/3628034.3628043(1-9)Online publication date: 5-Jul-2023
https://dl.acm.org/doi/10.1145/3628034.3628043
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Index Terms

FORMS: a formal reference model for self-adaptation
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

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Published In

ICAC '10: Proceedings of the 7th international conference on Autonomic computing

June 2010

246 pages

ISBN:9781450300742

DOI:10.1145/1809049

General Chair:
Manish Parashar
Rutgers University, USA
,
Program Chairs:
Renato Figueiredo
University of Florida, USA
,
Emre Kıcıman
Microsoft Research, USA

Copyright © 2010 ACM.

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Published: 07 June 2010

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ICAC '10: 7th International Conference on Autonomic Computing

June 7 - 11, 2010

DC, Washington, USA

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Cited By

Affonso FNagassaki Campos GGuiguer Menaldo G(2024)A Reference Architecture Based on Reflection for Self-Adaptive Software: A Second ReleaseIEEE Access10.1109/ACCESS.2024.342836812(97476-97499)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3428368
Weyns DBäck TVidal RYao XBelbachir A(2023)The vision of self-evolving computing systemsJournal of Integrated Design and Process Science10.3233/JID-22000326:3-4(351-367)Online publication date: 13-Oct-2023
https://doi.org/10.3233/JID-220003
Provoost MWeyns DVan Landuyt DMichiels SBureš T(2023)Joint Learning: A Pattern for Reliable and Efficient Decision-Making in Self-Adaptive Internet of ThingsProceedings of the 28th European Conference on Pattern Languages of Programs10.1145/3628034.3628043(1-9)Online publication date: 5-Jul-2023
https://dl.acm.org/doi/10.1145/3628034.3628043
Zia IBasit Ur Rahim MLiu THe Z(2023)Formal Modeling and Verification of Industrial Robotic Arm - A Case Study2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)10.1109/QRS-C60940.2023.00106(499-508)Online publication date: 22-Oct-2023
https://doi.org/10.1109/QRS-C60940.2023.00106
Kachi FBouanaka C(2023)A hybrid model for efficient decision-making in self-adaptive systemsInformation and Software Technology10.1016/j.infsof.2022.107063153:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.infsof.2022.107063
Abdul Basit Ur Rahim MAhsan Ur Raheem MSohail MFarid MMufti M(2023)Formal verification of reconfigurable systemsSoft Computing10.1007/s00500-023-08272-zOnline publication date: 6-May-2023
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Hachicha MBen Halima RKacem A(2022)Modeling Autonomic SystemsInternational Journal of Software Innovation10.4018/IJSI.30358510:1(1-22)Online publication date: 13-Jul-2022
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Quin FWeyns DGheibi O(2022)Reducing large adaptation spaces in self-adaptive systems using classical machine learningJournal of Systems and Software10.1016/j.jss.2022.111341190:COnline publication date: 1-Aug-2022
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Ismail SShah KReza HMarsh RGrant E(2021)Toward Management of Uncertainty in Self-Adaptive Software Systems: IoT Case StudyComputers10.3390/computers1003002710:3(27)Online publication date: 27-Feb-2021
https://doi.org/10.3390/computers10030027
Zegzhda DLavrova DPavlenko E(2020)Management of a Dynamic Infrastructure of Complex Systems Under Conditions of Directed Cyber AttacksJournal of Computer and Systems Sciences International10.1134/S106423072002012459:3(358-370)Online publication date: 12-Jul-2020
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