research-article

From means-end analysis to proactive means-end reasoning

Authors:

Luca Sabatucci,

Massimo CossentinoAuthors Info & Claims

SEAMS '15: Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Pages 2 - 12

Published: 16 May 2015 Publication History

Abstract

Self-adaptation is a prominent property for developing complex distributed software systems. Notable approaches to deal with self-adaptation are the runtime goal model artifacts. Goals are generally invariant along the system lifecycle but contain points of variability for allowing the system to decide among many alternative behaviors.

This work investigates how it is possible to provide goal models at run-time that do not contain tasks, i.e. the description of how to address goals, thus breaking the design-time tie up between Tasks and Goals, generally outcome of a means-end analysis. In this vision the system is up to decide how to combine its available Capabilities: the Proactive Means-End Reasoning.

The impact of this research line is to implement a goal-oriented form of self-adaptation where goal models can be injected at runtime. The paper also introduces MUSA, a Middleware for User-driven Service self-Adaptation.

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Cleland-Huang JAgrawal AVierhauser MMurphy MPrieto MSchmerl BMaggio MCámara J(2022)Extending MAPE-K to support human-machine teamingProceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3524844.3528054(120-131)Online publication date: 18-May-2022
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Sabatucci LCossentino M(2019)Supporting Dynamic Workflows with Automatic Extraction of Goals from BPMNACM Transactions on Autonomous and Adaptive Systems10.1145/335548814:2(1-38)Online publication date: 17-Oct-2019
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From means-end analysis to proactive means-end reasoning

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cover image ACM Conferences

SEAMS '15: Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

May 2015

186 pages

Conference Chair:
Paola Inverardi
University of L'Aquila, Italy
,
Program Chair:
Bradley Schmerl
Carnegie Mellon University

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ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS\DATC: IEEE Computer Society
TCSE: IEEE Computer Society's Tech. Council on Software Engin.

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IEEE Press

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Published: 16 May 2015

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ICSE '15: 37th International Conference on Software Engineering

May 16 - 24, 2015

Florence, Italy

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Overall Acceptance Rate 17 of 31 submissions, 55%

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Cited By

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https://dl.acm.org/doi/10.1145/3618001
Cleland-Huang JAgrawal AVierhauser MMurphy MPrieto MSchmerl BMaggio MCámara J(2022)Extending MAPE-K to support human-machine teamingProceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3524844.3528054(120-131)Online publication date: 18-May-2022
https://dl.acm.org/doi/10.1145/3524844.3528054
Sabatucci LCossentino M(2019)Supporting Dynamic Workflows with Automatic Extraction of Goals from BPMNACM Transactions on Autonomous and Adaptive Systems10.1145/335548814:2(1-38)Online publication date: 17-Oct-2019
https://dl.acm.org/doi/10.1145/3355488
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https://dl.acm.org/doi/10.1007/s10270-018-00712-x
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Incerto ETribastone MTrubiani C(2016)Symbolic performance adaptationProceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/2897053.2897060(140-150)Online publication date: 14-May-2016
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