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310 results on '"Schmerl, Bradley"'

1. Generative Manufacturing: A requirements and resource-driven approach to part making

Author

Chen, Hongrui, Joglekar, Aditya, Rubinstein, Zack, Schmerl, Bradley, Fedder, Gary, de Nijs, Jan, Garlan, David, Smith, Stephen, and Kara, Levent Burak

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

Advances in CAD and CAM have enabled engineers and design teams to digitally design parts with unprecedented ease. Software solutions now come with a range of modules for optimizing designs for performance requirements, generating instructions for manufacturing, and digitally tracking the entire process from design to procurement in the form of product life-cycle management tools. However, existing solutions force design teams and corporations to take a primarily serial approach where manufacturing and procurement decisions are largely contingent on design, rather than being an integral part of the design process. In this work, we propose a new approach to part making where design, manufacturing, and supply chain requirements and resources can be jointly considered and optimized. We present the Generative Manufacturing compiler that accepts as input the following: 1) An engineering part requirements specification that includes quantities such as loads, domain envelope, mass, and compliance, 2) A business part requirements specification that includes production volume, cost, and lead time, 3) Contextual knowledge about the current manufacturing state such as availability of relevant manufacturing equipment, materials, and workforce, both locally and through the supply chain. Based on these factors, the compiler generates and evaluates manufacturing process alternatives and the optimal derivative designs that are implied by each process, and enables a user guided iterative exploration of the design space. As part of our initial implementation of this compiler, we demonstrate the effectiveness of our approach on examples of a cantilever beam problem and a rocket engine mount problem and showcase its utility in creating and selecting optimal solutions according to the requirements and resources.

Published
2024

2. Understanding Misconfigurations in ROS: An Empirical Study and Current Approaches

Author

Canelas, Paulo, Schmerl, Bradley, Fonseca, Alcides, and Timperley, Christopher S.

Subjects
Computer Science - Software Engineering, Computer Science - Robotics
Abstract

The Robot Operating System (ROS) is a popular framework and ecosystem that allows developers to build robot software systems from reusable, off-the-shelf components. Systems are often built by customizing and connecting components via configuration files. While reusable components theoretically allow rapid prototyping, ensuring proper configuration and connection is challenging, as evidenced by numerous questions on developer forums. Developers must abide to the often unchecked and unstated assumptions of individual components. Failure to do so can result in misconfigurations that are only discovered during field deployment, at which point errors may lead to unpredictable and dangerous behavior. Despite misconfigurations having been studied in the broader context of software engineering, robotics software (and ROS in particular) poses domain-specific challenges with potentially disastrous consequences. To understand and improve the reliability of ROS projects, it is critical to identify the types of misconfigurations faced by developers. To that end, we perform a study of ROS Answers, a Q&A platform, to identify and categorize misconfigurations that occur during ROS development. We then conduct a literature review to assess the coverage of these misconfigurations by existing detection techniques. In total, we find 12 high-level categories and 50 sub-categories of misconfigurations. Of these categories, 27 are not covered by existing techniques. To conclude, we discuss how to tackle those misconfigurations in future work., Comment: 13 pages

Published
2024
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3. CURE: Simulation-Augmented Auto-Tuning in Robotics

Author

Hossen, Md Abir, Kharade, Sonam, O'Kane, Jason M., Schmerl, Bradley, Garlan, David, and Jamshidi, Pooyan

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Robotic systems are typically composed of various subsystems, such as localization and navigation, each encompassing numerous configurable components (e.g., selecting different planning algorithms). Once an algorithm has been selected for a component, its associated configuration options must be set to the appropriate values. Configuration options across the system stack interact non-trivially. Finding optimal configurations for highly configurable robots to achieve desired performance poses a significant challenge due to the interactions between configuration options across software and hardware that result in an exponentially large and complex configuration space. These challenges are further compounded by the need for transferability between different environments and robotic platforms. Data efficient optimization algorithms (e.g., Bayesian optimization) have been increasingly employed to automate the tuning of configurable parameters in cyber-physical systems. However, such optimization algorithms converge at later stages, often after exhausting the allocated budget (e.g., optimization steps, allotted time) and lacking transferability. This paper proposes CURE -- a method that identifies causally relevant configuration options, enabling the optimization process to operate in a reduced search space, thereby enabling faster optimization of robot performance. CURE abstracts the causal relationships between various configuration options and robot performance objectives by learning a causal model in the source (a low-cost environment such as the Gazebo simulator) and applying the learned knowledge to perform optimization in the target (e.g., Turtlebot 3 physical robot). We demonstrate the effectiveness and transferability of CURE by conducting experiments that involve varying degrees of deployment changes in both physical robots and simulation., Comment: Revised submission in IEEE Transactions on Robotics (T-RO), 2024

Published
2024

4. CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots

Author

Hossen, Md Abir, Kharade, Sonam, Schmerl, Bradley, Cámara, Javier, O'Kane, Jason M., Czaplinski, Ellen C., Dzurilla, Katherine A., Garlan, David, and Jamshidi, Pooyan

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Robotic systems have subsystems with a combinatorially large configuration space and hundreds or thousands of possible software and hardware configuration options interacting non-trivially. The configurable parameters are set to target specific objectives, but they can cause functional faults when incorrectly configured. Finding the root cause of such faults is challenging due to the exponentially large configuration space and the dependencies between the robot's configuration settings and performance. This paper proposes CaRE -- a method for diagnosing the root cause of functional faults through the lens of causality. CaRE abstracts the causal relationships between various configuration options and the robot's performance objectives by learning a causal structure and estimating the causal effects of options on robot performance indicators. We demonstrate CaRE's efficacy by finding the root cause of the observed functional faults and validating the diagnosed root cause by conducting experiments in both physical robots (Husky and Turtlebot 3) and in simulation (Gazebo). Furthermore, we demonstrate that the causal models learned from robots in simulation (e.g., Husky in Gazebo) are transferable to physical robots across different platforms (e.g., Husky and Turtlebot 3)., Comment: IEEE Robotics and Automation Letters, 2023 (Accepted)

Published
2023

5. Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation

Author

Weyns, Danny, Gerostathopoulos, Ilias, Buhnova, Barbora, Cardozo, Nicolas, Cioroaica, Emilia, Dusparic, Ivana, Grunske, Lars, Jamshidi, Pooyan, Julien, Christine, Michael, Judith, Moreno, Gabriel, Nejati, Shiva, Pelliccione, Patrizio, Quin, Federico, Rodrigues, Genaina, Schmerl, Bradley, Vieira, Marco, Vogel, Thomas, and Wohlrab, Rebekka

Subjects
Computer Science - Software Engineering
Abstract

Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive systems. While these artifacts have shown their value, it is not clear to what extent these artifacts support research on problems in self-adaptation that are relevant to industry. This paper provides a set of guidelines for artifacts that aim at supporting industry-relevant research on self-adaptation. The guidelines that are grounded on data obtained from a survey with practitioners were derived during working sessions at the 17th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. Artifact providers can use the guidelines for aligning future artifacts with industry needs; they can also be used to evaluate the industrial relevance of existing artifacts. We also propose an artifact template., Comment: 7 pages

Published
2022

7. Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning

Author

Weyns, Danny, Schmerl, Bradley, Kishida, Masako, Leva, Alberto, Litoiu, Marin, Ozay, Necmiye, Paterson, Colin, and Tei, Kenji

Subjects
Computer Science - Software Engineering, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

Two established approaches to engineer adaptive systems are architecture-based adaptation that uses a Monitor-Analysis-Planning-Executing (MAPE) loop that reasons over architectural models (aka Knowledge) to make adaptation decisions, and control-based adaptation that relies on principles of control theory (CT) to realize adaptation. Recently, we also observe a rapidly growing interest in applying machine learning (ML) to support different adaptation mechanisms. While MAPE and CT have particular characteristics and strengths to be applied independently, in this paper, we are concerned with the question of how these approaches are related with one another and whether combining them and supporting them with ML can produce better adaptive systems. We motivate the combined use of different adaptation approaches using a scenario of a cloud-based enterprise system and illustrate the analysis when combining the different approaches. To conclude, we offer a set of open questions for further research in this interesting area., Comment: 7 pages

Published
2021

8. Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots

Author

Jamshidi, Pooyan, Cámara, Javier, Schmerl, Bradley, Kästner, Christian, and Garlan, David

Subjects
Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract

Modern cyber-physical systems (e.g., robotics systems) are typically composed of physical and software components, the characteristics of which are likely to change over time. Assumptions about parts of the system made at design time may not hold at run time, especially when a system is deployed for long periods (e.g., over decades). Self-adaptation is designed to find reconfigurations of systems to handle such run-time inconsistencies. Planners can be used to find and enact optimal reconfigurations in such an evolving context. However, for systems that are highly configurable, such planning becomes intractable due to the size of the adaptation space. To overcome this challenge, in this paper we explore an approach that (a) uses machine learning to find Pareto-optimal configurations without needing to explore every configuration and (b) restricts the search space to such configurations to make planning tractable. We explore this in the context of robot missions that need to consider task timeliness and energy consumption. An independent evaluation shows that our approach results in high-quality adaptation plans in uncertain and adversarial environments., Comment: 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2019 )

Published
2019

12. Explaining Architectural Design Tradeoff Spaces: A Machine Learning Approach

Author

Cámara, Javier, Silva, Mariana, Garlan, David, Schmerl, Bradley, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Biffl, Stefan, editor, Navarro, Elena, editor, Löwe, Welf, editor, Sirjani, Marjan, editor, Mirandola, Raffaela, editor, and Weyns, Danny, editor

Published
2021
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14. Automated Planning for Supporting Knowledge-Intensive Processes

Author

Venero, Sheila Katherine, Schmerl, Bradley, Montecchi, Leonardo, dos Reis, Julio Cesar, Rubira, Cecília Mary Fischer, van der Aalst, Wil, Series Editor, Mylopoulos, John, Series Editor, Rosemann, Michael, Series Editor, Shaw, Michael J., Series Editor, Szyperski, Clemens, Series Editor, Nurcan, Selmin, editor, Reinhartz-Berger, Iris, editor, Soffer, Pnina, editor, and Zdravkovic, Jelena, editor

Published
2020
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17. Foundations and Tools for End-User Architecting

Author

Garlan, David, Dwivedi, Vishal, Ruchkin, Ivan, and Schmerl, Bradley

Subjects
Computer Science - Software Engineering, Computer Science - Human-Computer Interaction, Computer Science - Social and Information Networks, D.2.11, H.5.2
Abstract

Within an increasing number of domains an important emerging need is the ability for technically naive users to compose computational elements into novel configurations. Examples include astronomers who create new analysis pipelines to process telescopic data, intelligence analysts who must process diverse sources of unstructured text to discover socio-technical trends, and medical researchers who have to process brain image data in new ways to understand disease pathways. Creating such compositions today typically requires low-level technical expertise, limiting the use of computational methods and increasing the cost of using them. In this paper we describe an approach - which we term end-user architecting - that exploits the similarity between such compositional activities and those of software architects. Drawing on the rich heritage of software architecture languages, methods, and tools, we show how those techniques can be adapted to support end users in composing rich computational systems through domain-specific compositional paradigms and component repositories, without requiring that they have knowledge of the low-level implementation details of the components or the compositional infrastructure. Further, we outline a set of open research challenges that the area of end-user architecting raises.

Published
2012
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19. IPL: An Integration Property Language for Multi-model Cyber-physical Systems

Author

Ruchkin, Ivan, Sunshine, Joshua, Iraci, Grant, Schmerl, Bradley, Garlan, David, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Havelund, Klaus, editor, Peleska, Jan, editor, Roscoe, Bill, editor, and de Vink, Erik, editor

Published
2018
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20. Reasoning About Sensing Uncertainty in Decision-Making for Self-adaptation

Author

Cámara, Javier, Peng, Wenxin, Garlan, David, Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Cerone, Antonio, editor, and Roveri, Marco, editor

Published
2018
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22. Software Engineering for Self-Adaptive Systems: Research Challenges in the Provision of Assurances

Author

de Lemos, Rogério, Garlan, David, Ghezzi, Carlo, Giese, Holger, Andersson, Jesper, Litoiu, Marin, Schmerl, Bradley, Weyns, Danny, Baresi, Luciano, Bencomo, Nelly, Brun, Yuriy, Camara, Javier, Calinescu, Radu, Cohen, Myra B., Gorla, Alessandra, Grassi, Vincenzo, Grunske, Lars, Inverardi, Paola, Jezequel, Jean-Marc, Malek, Sam, Mirandola, Raffaela, Mori, Marco, Müller, Hausi A., Rouvoy, Romain, Rubira, Cecília M. F., Rutten, Eric, Shaw, Mary, Tamburrelli, Giordano, Tamura, Gabriel, Villegas, Norha M., Vogel, Thomas, Zambonelli, Franco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, de Lemos, Rogério, editor, Garlan, David, editor, Ghezzi, Carlo, editor, and Giese, Holger, editor

Published
2017
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23. Analyzing Self-Adaptation Via Model Checking of Stochastic Games

Author

Cámara, Javier, Garlan, David, Moreno, Gabriel A., Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, de Lemos, Rogério, editor, Garlan, David, editor, Ghezzi, Carlo, editor, and Giese, Holger, editor

Published
2017
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24. Challenges in Composing and Decomposing Assurances for Self-Adaptive Systems

Author

Schmerl, Bradley, Andersson, Jesper, Vogel, Thomas, Cohen, Myra B., Rubira, Cecilia M. F., Brun, Yuriy, Gorla, Alessandra, Zambonelli, Franco, Baresi, Luciano, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, de Lemos, Rogério, editor, Garlan, David, editor, Ghezzi, Carlo, editor, and Giese, Holger, editor

Published
2017
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25. Synthesis and Quantitative Verification of Tradeoff Spaces for Families of Software Systems

Author

Cámara, Javier, Garlan, David, Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lopes, Antónia, editor, and de Lemos, Rogério, editor

Published
2017
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27. Architecture Modeling and Analysis of Security in Android Systems

Author

Schmerl, Bradley, Gennari, Jeff, Sadeghi, Alireza, Bagheri, Hamid, Malek, Sam, Cámara, Javier, Garlan, David, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tekinerdogan, Bedir, editor, Zdun, Uwe, editor, and Babar, Ali, editor

Published
2016
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32. Impact Models for Architecture-Based Self-adaptive Systems

Author

Moreno, Javier Cámara, Lopes, Antónia, Garlan, David, Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lanese, Ivan, editor, and Madelaine, Eric, editor

Published
2015
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33. Resolving Data Mismatches in End-User Compositions

Author

Velasco-Elizondo, Perla, Dwivedi, Vishal, Garlan, David, Schmerl, Bradley, Fernandes, José Maria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Dittrich, Yvonne, editor, Burnett, Margaret, editor, Mørch, Anders, editor, and Redmiles, David, editor

Published
2013
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34. On Patterns for Decentralized Control in Self-Adaptive Systems

Author

Weyns, Danny, Schmerl, Bradley, Grassi, Vincenzo, Malek, Sam, Mirandola, Raffaela, Prehofer, Christian, Wuttke, Jochen, Andersson, Jesper, Giese, Holger, Göschka, Karl M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, de Lemos, Rogério, editor, Giese, Holger, editor, Müller, Hausi A., editor, and Shaw, Mary, editor

Published
2013
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35. Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

Author

de Lemos, Rogério, Giese, Holger, Müller, Hausi A., Shaw, Mary, Andersson, Jesper, Litoiu, Marin, Schmerl, Bradley, Tamura, Gabriel, Villegas, Norha M., Vogel, Thomas, Weyns, Danny, Baresi, Luciano, Becker, Basil, Bencomo, Nelly, Brun, Yuriy, Cukic, Bojan, Desmarais, Ron, Dustdar, Schahram, Engels, Gregor, Geihs, Kurt, Göschka, Karl M., Gorla, Alessandra, Grassi, Vincenzo, Inverardi, Paola, Karsai, Gabor, Kramer, Jeff, Lopes, Antónia, Magee, Jeff, Malek, Sam, Mankovskii, Serge, Mirandola, Raffaela, Mylopoulos, John, Nierstrasz, Oscar, Pezzè, Mauro, Prehofer, Christian, Schäfer, Wilhelm, Schlichting, Rick, Smith, Dennis B., Sousa, João Pedro, Tahvildari, Ladan, Wong, Kenny, Wuttke, Jochen, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, de Lemos, Rogério, editor, Giese, Holger, editor, Müller, Hausi A., editor, and Shaw, Mary, editor

Published
2013
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36. Architecture-Based Run-Time Fault Diagnosis

Author

Casanova, Paulo, Schmerl, Bradley, Garlan, David, Abreu, Rui, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Crnkovic, Ivica, editor, Gruhn, Volker, editor, and Book, Matthias, editor

Published
2011
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37. An Architectural Approach to End User Orchestrations

Author

Dwivedi, Vishal, Velasco-Elizondo, Perla, Maria Fernandes, Jose, Garlan, David, Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Crnkovic, Ivica, editor, Gruhn, Volker, editor, and Book, Matthias, editor

Published
2011
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41. Improving Architecture-Based Self-adaptation Using Preemption

Author

Raheja, Rahul, Cheng, Shang-Wen, Garlan, David, Schmerl, Bradley, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Weyns, Danny, editor, Malek, Sam, editor, de Lemos, Rogério, editor, and Andersson, Jesper, editor

Published
2010
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42. Improving Architecture-Based Self-Adaptation through Resource Prediction

Author

Cheng, Shang-Wen, Poladian, Vahe V., Garlan, David, Schmerl, Bradley, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Cheng, Betty H. C., editor, de Lemos, Rogério, editor, Giese, Holger, editor, Inverardi, Paola, editor, and Magee, Jeff, editor

Published
2009
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46. Focusing on What Matters: Explaining Quality Tradeoffs in Software-Intensive Systems Via Dimensionality Reduction

Author

Camara, Javier, Wohlrab, Rebekka, Garlan, David, and Schmerl, Bradley

Abstract

Building and operating software-intensive systems involves exploring decision spaces composed of large numbers of variables and their complex relations. We report on using dimensionality reduction techniques that enable decision makers in different domains to focus on crucial elements of the decision space.

Published
2024
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47. Making Self-Adaptation an Engineering Reality

Author

Cheng, Shang-Wen, Garlan, David, Schmerl, Bradley, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Babaoglu, Ozalp, editor, Jelasity, Márk, editor, Montresor, Alberto, editor, Fetzer, Christof, editor, Leonardi, Stefano, editor, van Moorsel, Aad, editor, and van Steen, Maarten, editor

Published
2005
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49. Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation

Author

Weyns, Danny, primary, Gerostathopoulos, Ilias, additional, Buhnova, Barbora, additional, Cardozo, Nicolás, additional, Cioroaica, Emilia, additional, Dusparic, Ivana, additional, Grunske, Lars, additional, Jamshidi, Pooyan, additional, Julien, Christine, additional, Michael, Judith, additional, Moreno, Gabriel, additional, Nejati, Shiva, additional, Pelliccione, Patrizio, additional, Quin, Federico, additional, Rodrigues, Genaina, additional, Schmerl, Bradley, additional, Vieira, Marco, additional, Vogel, Thomas, additional, and Wohlrab, Rebekka, additional

Published
2022
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50. Using Architectural Models at Runtime: Research Challenges

Author

Garlan, David, Schmerl, Bradley, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Oquendo, Flavio, editor, Warboys, Brian C., editor, and Morrison, Ron, editor

Published
2004
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