The Experts below are selected from a list of 53778 Experts worldwide ranked by ideXlab platform
Howie Shrobe - One of the best experts on this subject based on the ideXlab platform.
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IWSAS - Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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IWSAS - Introduction to self-Adaptive Software: applications
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17- 19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
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Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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Introduction to self-Adaptive Software: Applications
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17-19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
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Results of the second international workshop on self-Adaptive Software
Lecture Notes in Computer Science, 2001Co-Authors: Robert Laddaga, Paul Roberston, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17-19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This paper reports on the results of three workshop sessions held on the topics of applications, research needed and design patterns, all for self Adaptive Software.
Robert Laddaga - One of the best experts on this subject based on the ideXlab platform.
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Self Adaptive Software Problems and Projects
2006 Second International IEEE Workshop on Software Evolvability (SE'06), 2006Co-Authors: Robert LaddagaAbstract:Self Adaptive Software is a relatively new approach to dynamic self management of Software based systems. This paper discusses the concepts, history and applications of Self Adaptive Software over the past ten years. It also presents a set of crucial research problems for the next ten years of research in this area.
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IWSAS - Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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IWSAS - Introduction to self-Adaptive Software: applications
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17- 19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
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Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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Introduction to self-Adaptive Software: Applications
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17-19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
Sam Malek - One of the best experts on this subject based on the ideXlab platform.
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uncertainty in self Adaptive Software systems
Lecture Notes in Computer Science, 2013Co-Authors: Naeem Esfahani, Sam MalekAbstract:The ever-growing complexity of Software systems coupled with their stringent availability requirements are challenging the manual management of Software after its deployment. This has motivated the development of self-Adaptive Software systems. Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior at runtime. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world applications. Uncertainty in this setting is a vaguely understood term. In this paper, we characterize the sources of uncertainty in self-Adaptive Software system, and demonstrate its impact on the system’s ability to satisfy its objectives. We then provide an alternative notion of optimality that explicitly incorporates the uncertainty underlying the knowledge (models) used for decision making. We discuss the state-of-the-art for dealing with uncertainty in this setting, and conclude with a set of challenges, which provide a road map for future research.
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Software Engineering for Self-Adaptive Systems - Uncertainty in Self-Adaptive Software Systems
Software Engineering for Self-Adaptive Systems II, 2013Co-Authors: Naeem Esfahani, Sam MalekAbstract:The ever-growing complexity of Software systems coupled with their stringent availability requirements are challenging the manual management of Software after its deployment. This has motivated the development of self-Adaptive Software systems. Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior at runtime. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world applications. Uncertainty in this setting is a vaguely understood term. In this paper, we characterize the sources of uncertainty in self-Adaptive Software system, and demonstrate its impact on the system’s ability to satisfy its objectives. We then provide an alternative notion of optimality that explicitly incorporates the uncertainty underlying the knowledge (models) used for decision making. We discuss the state-of-the-art for dealing with uncertainty in this setting, and conclude with a set of challenges, which provide a road map for future research.
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A Learning-Based Framework for Engineering Feature-Oriented Self-Adaptive Software Systems
IEEE Transactions on Software Engineering, 2013Co-Authors: Naeem Esfahani, Ahmed Elkhodary, Sam MalekAbstract:Self-Adaptive Software systems are capable of adjusting their behavior at runtime to achieve certain functional or quality-of-service goals. Often a representation that reflects the internal structure of the managed system is used to reason about its characteristics and make the appropriate adaptation decisions. However, runtime conditions can radically change the internal structure in ways that were not accounted for during their design. As a result, unanticipated changes at runtime that violate the assumptions made about the internal structure of the system could degrade the accuracy of the adaptation decisions. We present an approach for engineering self-Adaptive Software systems that brings about two innovations: 1) a feature-oriented approach for representing engineers' knowledge of adaptation choices that are deemed practical, and 2) an online learning-based approach for assessing and reasoning about adaptation decisions that does not require an explicit representation of the internal structure of the managed Software system. Engineers' knowledge, represented in feature-models, adds structure to learning, which in turn makes online learning feasible. We present an empirical evaluation of the framework using a real-world self-Adaptive Software system. Results demonstrate the framework's ability to accurately learn the changing dynamics of the system while achieving efficient analysis and adaptation.
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taming uncertainty in self Adaptive Software
Foundations of Software Engineering, 2011Co-Authors: Naeem Esfahani, Ehsan Kouroshfar, Sam MalekAbstract:Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation decisions. This has been one of the key obstacles to wide-spread adoption of self-adaption techniques in risk-averse real-world settings. In this paper, we describe an approach, called POssIbilistic SElf-aDaptation (POISED), for tackling the challenge posed by uncertainty in making adaptation decisions. POISED builds on possibility theory to assess both the positive and negative consequences of uncertainty. It makes adaptation decisions that result in the best range of potential behavior. We demonstrate POISED's application to the problem of improving a Software system's quality of service via runtime reconfiguration of its customizable Software components. We have extensively evaluated POISED using a prototype of a robotic Software system.
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modeling dimensions of self Adaptive Software systems
Lecture Notes in Computer Science, 2009Co-Authors: Jesper Andersson, Sam Malek, Rogerio De Lemos, Danny WeynsAbstract:It is commonly agreed that a self-Adaptive Software system is one that can modify itself at run-time due to changes in the system, its requirements, or the environment in which it is deployed. A cursory review of the Software engineering literature attests to the wide spectrum of Software systems that are described as self-Adaptive. The way self-adaptation is conceived depends on various aspects, such as the users' requirements, the particular properties of a system, and the characteristics of the environment. In this paper, we propose a classification of modeling dimensions for self-Adaptive Software systems. Each modeling dimension describes a particular facet of the system that is relevant to self-adaptation. The modeling dimensions provide the engineers with a common set of vocabulary for specifying the self-Adaptive properties under consideration and select suitable solutions. We illustrate how the modeling dimensions apply to several application scenarios.
Naeem Esfahani - One of the best experts on this subject based on the ideXlab platform.
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uncertainty in self Adaptive Software systems
Lecture Notes in Computer Science, 2013Co-Authors: Naeem Esfahani, Sam MalekAbstract:The ever-growing complexity of Software systems coupled with their stringent availability requirements are challenging the manual management of Software after its deployment. This has motivated the development of self-Adaptive Software systems. Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior at runtime. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world applications. Uncertainty in this setting is a vaguely understood term. In this paper, we characterize the sources of uncertainty in self-Adaptive Software system, and demonstrate its impact on the system’s ability to satisfy its objectives. We then provide an alternative notion of optimality that explicitly incorporates the uncertainty underlying the knowledge (models) used for decision making. We discuss the state-of-the-art for dealing with uncertainty in this setting, and conclude with a set of challenges, which provide a road map for future research.
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Software Engineering for Self-Adaptive Systems - Uncertainty in Self-Adaptive Software Systems
Software Engineering for Self-Adaptive Systems II, 2013Co-Authors: Naeem Esfahani, Sam MalekAbstract:The ever-growing complexity of Software systems coupled with their stringent availability requirements are challenging the manual management of Software after its deployment. This has motivated the development of self-Adaptive Software systems. Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior at runtime. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world applications. Uncertainty in this setting is a vaguely understood term. In this paper, we characterize the sources of uncertainty in self-Adaptive Software system, and demonstrate its impact on the system’s ability to satisfy its objectives. We then provide an alternative notion of optimality that explicitly incorporates the uncertainty underlying the knowledge (models) used for decision making. We discuss the state-of-the-art for dealing with uncertainty in this setting, and conclude with a set of challenges, which provide a road map for future research.
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A Learning-Based Framework for Engineering Feature-Oriented Self-Adaptive Software Systems
IEEE Transactions on Software Engineering, 2013Co-Authors: Naeem Esfahani, Ahmed Elkhodary, Sam MalekAbstract:Self-Adaptive Software systems are capable of adjusting their behavior at runtime to achieve certain functional or quality-of-service goals. Often a representation that reflects the internal structure of the managed system is used to reason about its characteristics and make the appropriate adaptation decisions. However, runtime conditions can radically change the internal structure in ways that were not accounted for during their design. As a result, unanticipated changes at runtime that violate the assumptions made about the internal structure of the system could degrade the accuracy of the adaptation decisions. We present an approach for engineering self-Adaptive Software systems that brings about two innovations: 1) a feature-oriented approach for representing engineers' knowledge of adaptation choices that are deemed practical, and 2) an online learning-based approach for assessing and reasoning about adaptation decisions that does not require an explicit representation of the internal structure of the managed Software system. Engineers' knowledge, represented in feature-models, adds structure to learning, which in turn makes online learning feasible. We present an empirical evaluation of the framework using a real-world self-Adaptive Software system. Results demonstrate the framework's ability to accurately learn the changing dynamics of the system while achieving efficient analysis and adaptation.
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taming uncertainty in self Adaptive Software
Foundations of Software Engineering, 2011Co-Authors: Naeem Esfahani, Ehsan Kouroshfar, Sam MalekAbstract:Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation decisions. This has been one of the key obstacles to wide-spread adoption of self-adaption techniques in risk-averse real-world settings. In this paper, we describe an approach, called POssIbilistic SElf-aDaptation (POISED), for tackling the challenge posed by uncertainty in making adaptation decisions. POISED builds on possibility theory to assess both the positive and negative consequences of uncertainty. It makes adaptation decisions that result in the best range of potential behavior. We demonstrate POISED's application to the problem of improving a Software system's quality of service via runtime reconfiguration of its customizable Software components. We have extensively evaluated POISED using a prototype of a robotic Software system.
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ASE - A framework for managing uncertainty in self-Adaptive Software systems
2011 26th IEEE ACM International Conference on Automated Software Engineering (ASE 2011), 2011Co-Authors: Naeem EsfahaniAbstract:Self-adaptation endows a Software system with the ability to satisfy certain objectives by automatically modifying its behavior. While many promising approaches for the construction of self-Adaptive Software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation decisions. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world settings. In this research abstract I outline my ongoing effort in the development of a framework for managing uncertainty in self-adaptation. This framework employs state-of-the-art mathematical approaches to model and assess uncertainty in adaptation decisions. Preliminary results show that knowledge about uncertainty allows self-Adaptive Software systems to make better decisions.
Paul Robertson - One of the best experts on this subject based on the ideXlab platform.
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IWSAS - Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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IWSAS - Introduction to self-Adaptive Software: applications
Self-Adaptive Software: Applications, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17- 19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
-
Probabilistic dispatch, dynamic domain architecture, and self-Adaptive Software
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:In this paper we report on a beginning effort in the self Adaptive Software research area of improving function or method dispatch. We extend type-signature based method dispatch in a dynamic object oriented programming language with probabilistic dispatch, where the choice of method to use is determined by statistical means. This research direction is part of a larger self Adaptive Software effort at the MIT Artificial Intelligence Laboratory, called Dynamic Domain Architectures.
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Introduction to self-Adaptive Software: Applications
Lecture Notes in Computer Science, 2003Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17-19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This book presents the collection of papers delivered at this workshop, along with some related papers, and reports of the workshop activities.
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IWSAS - Results of the first international workshop on self Adaptive Software
2000Co-Authors: Robert Laddaga, Paul Robertson, Howie ShrobeAbstract:The second International Workshop on Self Adaptive Software was held on scenic Lake Balaton, in Hungary during May 17-19, 2001. The workshop was sponsored by the Technical University of Budapest, and organized by Gabor Peceli, Head of the Department of Measurement and Information Systems, assisted by Simon Gyula, Senior Lecturer in the department. This paper reports on the results of three workshop sessions held on the topics of applications, research needed and design patterns, all for self Adaptive Software.
