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Documents authored by Bures, Tomas

Document
DOI: 10.4230/DARTS.4.1.0
Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee

Authors: Tomas Bures, Danny Weyns, and Jesper Andersson

Published in: DARTS, Volume 4, Issue 1, Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018)

Abstract
Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee
Cite as

Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 1, pp. 0:i-0:xiii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{bures_et_al:DARTS.4.1.0,
  author =	{Bures, Tomas and Weyns, Danny and Andersson, Jesper},
  title =	{{ Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee}},
  pages =	{0:i--0:xiii},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2018},
  volume =	{4},
  number =	{1},
  editor =	{Bures, Tomas and Weyns, Danny and Andersson, Jesper},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.4.1.0},
  URN =		{urn:nbn:de:0030-drops-87096},
  doi =		{10.4230/DARTS.4.1.0},
  annote =	{Keywords: Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee}
}
Document
DOI: 10.4230/DARTS.3.1.5
Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact)

Authors: Sanny Schmid, Ilias Gerostathopoulos, Christian Prehofer, and Tomas Bures

Published in: DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)

Abstract
This artifact supports our research in self-adaptation in large-scale software-intensive distributed systems. The main problem in making such systems self-adaptive is that their adaptation needs to consider the current situation in the whole system. However, developing a complete and accurate model of such systems at design time is very challenging. We are instead investigating a novel approach where the system model consists only of the essential input and output parameters and Big Data analytics is used to guide self-adaptation based on a continuous stream of operational data. In this artifact, we provide a concrete model problem that can be used as a case study for evaluating different self-adaptation techniques pertinent to complex large-scale distributed systems. We also provide an extensible tool-based framework for endorsing an arbitrary system with self-adaptation based on analysis of operational data coming from the system. The model problem (CrowdNav) and the framework (RTX) have been packaged together in this artifact, but can also work independently.
Cite as

Sanny Schmid, Ilias Gerostathopoulos, Christian Prehofer, and Tomas Bures. Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact). In Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017). Dagstuhl Artifacts Series (DARTS), Volume 3, Issue 1, pp. 5:1-5:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{schmid_et_al:DARTS.3.1.5,
  author =	{Schmid, Sanny and Gerostathopoulos, Ilias and Prehofer, Christian and Bures, Tomas},
  title =	{{Model Problem (CrowdNav) and Framework (RTX) for Self-Adaptation Based on Big Data Analytics (Artifact)}},
  pages =	{5:1--5:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  editor =	{Schmid, Sanny and Gerostathopoulos, Ilias and Prehofer, Christian and Bures, Tomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.3.1.5},
  URN =		{urn:nbn:de:0030-drops-71435},
  doi =		{10.4230/DARTS.3.1.5},
  annote =	{Keywords: self-adaptation; Big Data analytics; model problem, tool, framework}
}
Document
DOI: 10.4230/DARTS.3.1.6
Intelligent Ensembles – a Declarative Group Description Language and Java Framework (Artifact)

Authors: Filip Krijt, Zbynek Jiracek, Tomas Bures, Petr Hnetynka, and Ilias Gerostathopoulos

Published in: DARTS, Volume 3, Issue 1, Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)

Abstract
Smart cyber-physical systems (sCPS) is a growing research field focused on scenarios such as smart cities or smart mobility, where autonomous components are deployed in a physical environment, and are expected to cooperate with one another, as well as with humans. As these systems typically operate in a highly uncertain and dynamically changing environment, being able to cooperate and adapt in groups to cope with various (possibly unanticipated) situations becomes a crucial and challenging task. In this artifact, we respond to this challenge by presenting the Intelligent Ensembles framework, consisting of a high-level declarative language for describing dynamic cooperation groups, and a Java runtime library for automatically forming groups that best satisfy the given specification. The framework provides dynamic architecture adaptation (i.e., forming groups of components and exchanging data between them) based on the state of components and situation in their environment. Further, the framework can be used as a first step of a group-wise adaptation (i.e., identifying components that are to negotiate and coordinate in an adaptation). The framework is built on top of the Z3 SMT solver and the Eclipse Modelling Framework.
Cite as

Filip Krijt, Zbynek Jiracek, Tomas Bures, Petr Hnetynka, and Ilias Gerostathopoulos. Intelligent Ensembles – a Declarative Group Description Language and Java Framework (Artifact). In Special Issue of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017). Dagstuhl Artifacts Series (DARTS), Volume 3, Issue 1, pp. 6:1-6:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@Article{krijt_et_al:DARTS.3.1.6,
  author =	{Krijt, Filip and Jiracek, Zbynek and Bures, Tomas and Hnetynka, Petr and Gerostathopoulos, Ilias},
  title =	{{Intelligent Ensembles – a Declarative Group Description Language and Java Framework (Artifact)}},
  pages =	{6:1--6:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2017},
  volume =	{3},
  number =	{1},
  editor =	{Krijt, Filip and Jiracek, Zbynek and Bures, Tomas and Hnetynka, Petr and Gerostathopoulos, Ilias},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.3.1.6},
  URN =		{urn:nbn:de:0030-drops-71444},
  doi =		{10.4230/DARTS.3.1.6},
  annote =	{Keywords: Smart Cyber-physical Systems; Adaptive Architecture; Ensemble-based Component System; Group-wise Adaptation; Autonomic Systems}
}
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