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1. Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity

Author

Kiden, Sarah, Stahl, Bernd, Townsend, Beverley, Maple, Carsten, Vincent, Charles, Sampson, Fraser, Gilbert, Geoff, Smith, Helen, Deshmukh, Jayati, Ross, Jen, Williams, Jennifer, del Rincon, Jesus Martinez, Lisinska, Justyna, O'Shea, Karen, Abreu, Márjory Da Costa, Bencomo, Nelly, Deb, Oishi, Winter, Peter, Li, Phoebe, Torr, Philip, Lau, Pin Lean, Iniesta, Raquel, Ramchurn, Gopal, Stein, Sebastian, and Yazdanpanah, Vahid

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence
Abstract

This report presents a comprehensive response to the United Nation's Interim Report on Governing Artificial Intelligence (AI) for Humanity. It emphasizes the transformative potential of AI in achieving the Sustainable Development Goals (SDGs) while acknowledging the need for robust governance to mitigate associated risks. The response highlights opportunities for promoting equitable, secure, and inclusive AI ecosystems, which should be supported by investments in infrastructure and multi-stakeholder collaborations across jurisdictions. It also underscores challenges, including societal inequalities exacerbated by AI, ethical concerns, and environmental impacts. Recommendations advocate for legally binding norms, transparency, and multi-layered data governance models, alongside fostering AI literacy and capacity-building initiatives. Internationally, the report calls for harmonising AI governance frameworks with established laws, human rights standards, and regulatory approaches. The report concludes with actionable principles for fostering responsible AI governance through collaboration among governments, industry, academia, and civil society, ensuring the development of AI aligns with universal human values and the public good., Comment: Submitted to United Nations. 23 pages. All the Authors Contributed Equally

Published
2024

2. Abstraction Engineering

Author

Bencomo, Nelly, Cabot, Jordi, Chechik, Marsha, Cheng, Betty H. C., Combemale, Benoit, Wąsowski, Andrzej, and Zschaler, Steffen

Subjects
Computer Science - Software Engineering
Abstract

Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.

Published
2024

3. Approaching Unanticipated Consequences

Author

Darby, Andrew, Sawyer, Pete, and Bencomo, Nelly

Subjects
Computer Science - Software Engineering
Abstract

In an ever-changing world, even software that fulfils its requirements may have un-envisioned aftereffects with significant impacts. We explored how such impacts can be better understood at the pre-design phase in support of organisational preparedness. We considered three real-world case studies and engaged with literature from several disciplines to develop a conceptual framework. Across three workshops with industry practitioners and academics creative strategies from speculative design practices were used to prompt engagement with the framework. We found participant groups navigated the model with either a convergent or divergent intent. The academics, operating in an exploratory mode, came to a broad understanding of a class of technologies through its impacts. Operating in an anticipatory mode the industry practitioners came to a specific understanding of a technology's potential in their workplace. The study demonstrated potential for the conceptual framework to be used as a tool with implications for research and practice., Comment: 14 pages, 2 figures

Published
2023

4. A Framework for History-Aware Hyperparameter Optimisation in Reinforcement Learning

Author

Parra-Ullauri, Juan Marcelo, Zhen, Chen, García-Domínguez, Antonio, Bencomo, Nelly, Zheng, Changgang, Boubeta-Puig, Juan, Ortiz, Guadalupe, and Yang, Shufan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Software Engineering
Abstract

A Reinforcement Learning (RL) system depends on a set of initial conditions (hyperparameters) that affect the system's performance. However, defining a good choice of hyperparameters is a challenging problem. Hyperparameter tuning often requires manual or automated searches to find optimal values. Nonetheless, a noticeable limitation is the high cost of algorithm evaluation for complex models, making the tuning process computationally expensive and time-consuming. In this paper, we propose a framework based on integrating complex event processing and temporal models, to alleviate these trade-offs. Through this combination, it is possible to gain insights about a running RL system efficiently and unobtrusively based on data stream monitoring and to create abstract representations that allow reasoning about the historical behaviour of the RL system. The obtained knowledge is exploited to provide feedback to the RL system for optimising its hyperparameters while making effective use of parallel resources. We introduce a novel history-aware epsilon-greedy logic for hyperparameter optimisation that instead of using static hyperparameters that are kept fixed for the whole training, adjusts the hyperparameters at runtime based on the analysis of the agent's performance over time windows in a single agent's lifetime. We tested the proposed approach in a 5G mobile communications case study that uses DQN, a variant of RL, for its decision-making. Our experiments demonstrated the effects of hyperparameter tuning using history on training stability and reward values. The encouraging results show that the proposed history-aware framework significantly improved performance compared to traditional hyperparameter tuning approaches.

Published
2023

5. RDMSim: An Exemplar for Evaluation and Comparison of Decision-Making Techniques for Self-Adaptation

Author

Samin, Huma, Paucar, Luis H. Garcia, Bencomo, Nelly, Hurtado, Cesar M. Carranza, and Fredericks, Erik M.

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Decision-making for self-adaptation approaches need to address different challenges, including the quantification of the uncertainty of events that cannot be foreseen in advance and their effects, and dealing with conflicting objectives that inherently involve multi-objective decision making (e.g., avoiding costs vs. providing reliable service). To enable researchers to evaluate and compare decision-making techniques for self-adaptation, we present the RDMSim exemplar. RDMSim enables researchers to evaluate and compare techniques for decision-making under environmental uncertainty that support self-adaptation. The focus of the exemplar is on the domain problem related to Remote Data Mirroring, which gives opportunity to face the challenges described above. RDMSim provides probe and effector components for easy integration with external adaptation managers, which are associated with decision-making techniques and based on the MAPE-K loop. Specifically, the paper presents (i) RDMSim, a simulator for real-world experimentation, (ii) a set of realistic simulation scenarios that can be used for experimentation and comparison purposes, (iii) data for the sake of comparison., Comment: Accepted at the 16th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2021)

Published
2021

6. Agent-based Framework for Self-Organization of Collective and Autonomous Shuttle Fleets

Author

Bucchiarone, Antonio, De Sanctis, Martina, and Bencomo, Nelly

Subjects
Computer Science - Multiagent Systems
Abstract

The mobility of people is at the center of transportation planning and decision-making of the cities of the future. In order to accelerate the transition to zero-emissions and to maximize air quality benefits, smart cities are prioritizing walking, cycling, shared mobility services and public transport over the use of private cars. Extensive progress has been made in autonomous and electric cars. Autonomous Vehicles (AV) are increasingly capable of moving without full control of humans, automating some aspects of driving, such as steering or braking. For these reasons, cities are investing in the infrastructure and technology needed to support connected, multi-modal transit networks that include shared electric Autonomous Vehicles (AV). The relationship between traditional public transport and new mobility services is in the spotlight and need to be rethought. This paper proposes an agent-based simulation framework that allows for the creation and simulation of mobility scenarios to investigate the impact of new mobility modes on a city daily life. It lets traffic planners explore the cooperative integration of AV using a decentralized control approach. A prototype has been implemented and validated with data of the city of Trento., Comment: 13 pages, 10 Figures, Early Access Article published at the IEEE Transactions on Intelligent Transportation Systems

Published
2021
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7. Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead

Author

Bucchiarone, Antonio, Cicchetti, Antonio, Bencomo, Nelly, Loria, Enrica, and Marconi, Annapaola

Subjects
Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems
Abstract

Motivational digital systems offer capabilities to engage and motivate end-users to foster behavioral changes towards a common goal. In general these systems use gamification principles in non-games contexts. Over the years, gamification has gained consensus among researchers and practitioners as a tool to motivate people to perform activities with the ultimate goal of promoting behavioural change, or engaging the users to perform activities that can offer relevant benefits but which can be seen as unrewarding and even tedious. There exists a plethora of heterogeneous application scenarios towards reaching the common good that can benefit from gamification. However, an open problem is how to effectively combine multiple motivational campaigns to maximise the degree of participation without exposing the system to counterproductive behaviours. We conceive motivational digital systems as multi-agent systems: self-adaptation is a feature of the overall system, while individual agents may self-adapt in order to leverage other agents' resources, functionalities and capabilities to perform tasks more efficiently and effectively. Consequently, multiple campaigns can be run and adapted to reach common good. At the same time, agents are grouped into micro-communities in which agents contribute with their own social capital and leverage others' capabilities to balance their weaknesses. In this paper we propose our vision on how the principles at the base of the autonomous and multi-agent systems can be exploited to design multi-challenge motivational systems to engage smart communities towards common goals. We present an initial version of a general framework based on the MAPE-K loop and a set of research challenges that characterise our research roadmap for the implementation of our vision., Comment: 7 pages, 1 figure

Published
2021

8. Reward-Reinforced Reinforcement Learning for Multi-agent Systems

Author

Zheng, Changgang, Yang, Shufan, Parra-Ullauri, Juan, Garcia-Dominguez, Antonio, and Bencomo, Nelly

Subjects
Computer Science - Multiagent Systems
Abstract

Reinforcement learning algorithms in multi-agent systems deliver highly resilient and adaptable solutions for common problems in telecommunications,aerospace, and industrial robotics. However, achieving an optimal global goal remains a persistent obstacle for collaborative multi-agent systems, where learning affects the behaviour of more than one agent. A number of nonlinear function approximation methods have been proposed for solving the Bellman equation, which describe a recursive format of an optimal policy. However, how to leverage the value distribution based on reinforcement learning, and how to improve the efficiency and efficacy of such systems remain a challenge. In this work, we developed a reward-reinforced generative adversarial network to represent the distribution of the value function, replacing the approximation of Bellman updates. We demonstrated our method is resilient and outperforms other conventional reinforcement learning methods. This method is also applied to a practical case study: maximising the number of user connections to autonomous airborne base stations in a mobile communication network. Our method maximises the data likelihood using a cost function under which agents have optimal learned behaviours. This reward-reinforced generative adversarial network can be used as ageneric framework for multi-agent learning at the system level, Comment: 9 pages, 9 figures

Published
2021

9. Investigating the potential impact of values on requirements and software engineering

Author

Sutcliffe, Alistair, Sawyer, Pete, Liu, Wei, and Bencomo, Nelly

Subjects
Computer Science - Software Engineering, Computer Science - Computers and Society
Abstract

This paper describes an investigation into value-based software engineering and proposes a comprehensive value taxonomy with an interpretation of design feature implications. The value taxonomy is used to assess the design of Covid19 symptom tracker applications., Comment: ICSE SEIS 2021

Published
2021

11. Perpetual Assurances for Self-Adaptive Systems

Author

Weyns, Danny, Bencomo, Nelly, Calinescu, Radu, Cámara, Javier, Ghezzi, Carlo, Grassi, Vincenzo, Grunske, Lars, Inverardi, Paola, Jézéquel, Jean-Marc, Malek, Sam, Mirandola, Raffaela, Mori, Marco, and Tamburrelli, Giordano

Subjects
Computer Science - Software Engineering
Abstract

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an enduring process spanning the whole lifetime of the system. In this process, humans and the system jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for self-adaptive systems. In this paper, we provide a background framework and the foundation for perpetual assurances for self-adaptive systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation.

Published
2019

18. Decision Making for Self-Adaptation Based on Partially Observable Satisfaction of Non-Functional Requirements

Author

Garcia, Luis, Samin, Huma, Bencomo, Nelly, Garcia, Luis, Samin, Huma, and Bencomo, Nelly

Abstract

Approaches that support the decision-making of self-adaptive and autonomous systems (SAS) often consider an idealized situation where (i) the system’s state is treated as fully observable by the monitoring infrastructure, and (ii) adaptation actions are assumed to have known, deterministic effects over the system. However, in practice, the system’s state may not be fully observable, and the adaptation actions may produce unexpected effects due to uncertain factors. This article presents a novel probabilistic approach to quantify the uncertainty associated with the effects of adaptation actions on the state of a SAS. Supported by Bayesian inference and POMDPs (Partially-Observable Markov Decision Processes), these effects are translated into the satisfaction levels of the non-functional requirements (NFRs) to, therefore, drive the decision-making. The approach has been applied to two substantial case studies from the networking and Internet of Things (IoT) domains, using two different POMDP solvers. The results show that the approach delivers statistically significant improvements in supporting decision-making for SAS.

Published
2024

19. A MAPE-K approach to autonomic microservices

Author

Bucchiarone, Antonio, Guidi, Claudio, Lanese, Ivan, Bencomo, Nelly, Spillner, Josef, Bucchiarone, Antonio, Guidi, Claudio, Lanese, Ivan, Bencomo, Nelly, and Spillner, Josef

Abstract

Microservices are an emerging architectural style advocating for small loosely-coupled services in order to maximize scalability and adaptability. In order to help IT personnel, adaptability can be put (completely or partially) under the responsibility of the system using autonomic techniques, e.g., underpinned by a MAPE-K control loop. This paper discusses possible trade-offs, challenges, support techniques for software architects and research directions involved in building autonomic microservice-based systems.

Published
2024

20. Responsible AI governance: A response to UN interim report on governing AI for humanity

Author

Stahl, Bernd, Townsend, Beverley, Maple, Carsten, Vincent, Charles, Sampson, Fraser, Gilbert, Geoff, Smith, Helen, Deshmukh, Jayati, Ross, Jen, Williams, Jennifer, Martinez del Rincon, Jesus, Lisinska, Justyna, O'shea, Karen, Da Costa Abreu, Márjory, Bencomo, Nelly, Deb, Oishi, Winter, Peter, Li, Phoebe, Torr, Philip H. S., Lau, Pin Lean, Iniesta, Raquel, Kiden, Sarah, Ramchum, Sarvapali D., Stein, Sebastian, Yazdanpanah, Vahid, Stahl, Bernd, Townsend, Beverley, Maple, Carsten, Vincent, Charles, Sampson, Fraser, Gilbert, Geoff, Smith, Helen, Deshmukh, Jayati, Ross, Jen, Williams, Jennifer, Martinez del Rincon, Jesus, Lisinska, Justyna, O'shea, Karen, Da Costa Abreu, Márjory, Bencomo, Nelly, Deb, Oishi, Winter, Peter, Li, Phoebe, Torr, Philip H. S., Lau, Pin Lean, Iniesta, Raquel, Kiden, Sarah, Ramchum, Sarvapali D., Stein, Sebastian, and Yazdanpanah, Vahid

Published
2024

21. Opportunities in intelligent modeling assistance

Author

Mussbacher, Gunter, Combemale, Benoit, Kienzle, Jörg, Abrahão, Silvia, Ali, Hyacinth, Bencomo, Nelly, Búr, Márton, Burgueño, Loli, Engels, Gregor, Jeanjean, Pierre, Jézéquel, Jean-Marc, Kühn, Thomas, Mosser, Sébastien, Sahraoui, Houari, Syriani, Eugene, Varró, Dániel, and Weyssow, Martin

Published
2020
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22. Non-human Modelers: Challenges and Roadmap for Reusable Self-explanation

Author

Garcia-Dominguez, Antonio, Bencomo, Nelly, 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, Seidl, Martina, editor, and Zschaler, Steffen, editor

Published
2018
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25. Perpetual Assurances for Self-Adaptive Systems

Author

Weyns, Danny, Bencomo, Nelly, Calinescu, Radu, Camara, Javier, Ghezzi, Carlo, Grassi, Vincenzo, Grunske, Lars, Inverardi, Paola, Jezequel, Jean-Marc, Malek, Sam, Mirandola, Raffaela, Mori, Marco, Tamburrelli, Giordano, 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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26. 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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27. Self-modeling and Self-awareness

Author

Bellman, Kirstie L., Landauer, Christopher, Nelson, Phyllis, Bencomo, Nelly, Götz, Sebastian, Lewis, Peter, Esterle, Lukas, Kounev, Samuel, editor, Kephart, Jeffrey O., editor, Milenkoski, Aleksandar, editor, and Zhu, Xiaoyun, editor

Published
2017
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29. Self-aware Computing Systems: Related Concepts and Research Areas

Author

Cámara, Javier, Bellman, Kirstie L., Kephart, Jeffrey O., Autili, Marco, Bencomo, Nelly, Diaconescu, Ada, Giese, Holger, Götz, Sebastian, Inverardi, Paola, Kounev, Samuel, Tivoli, Massimo, Kounev, Samuel, editor, Kephart, Jeffrey O., editor, Milenkoski, Aleksandar, editor, and Zhu, Xiaoyun, editor

Published
2017
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30. The Notion of Self-aware Computing

Author

Kounev, Samuel, Lewis, Peter, Bellman, Kirstie L., Bencomo, Nelly, Camara, Javier, Diaconescu, Ada, Esterle, Lukas, Geihs, Kurt, Giese, Holger, Götz, Sebastian, Inverardi, Paola, Kephart, Jeffrey O., Zisman, Andrea, Kounev, Samuel, editor, Kephart, Jeffrey O., editor, Milenkoski, Aleksandar, editor, and Zhu, Xiaoyun, editor

Published
2017
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34. Living with Uncertainty in the Age of Runtime Models

Author

Giese, Holger, Bencomo, Nelly, Pasquale, Liliana, Ramirez, Andres J., Inverardi, Paola, Wätzoldt, Sebastian, Clarke, Siobhán, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, 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, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bencomo, Nelly, editor, France, Robert, editor, Cheng, Betty H. C., editor, and Aßmann, Uwe, editor

Published
2014
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35. Modular Specification of Self-Adaptive Systems with Models at Runtime using Relational Reference Attribute Grammars

Author

Aßmann, Uwe, Bencomo, Nelly, Castrillon, Jeronimo, Technische Universität Dresden, Schöne, René, Aßmann, Uwe, Bencomo, Nelly, Castrillon, Jeronimo, Technische Universität Dresden, and Schöne, René

Abstract

Adaptation enables a reaction to a changing environment. For traditional software development, that means changing the design and implementation of the software in a potentially complex and expensive process. If requirements are not known until the runtime of a software system, this system must be able to cope with changes during its runtime. For this, self-adaptive systems (SAS) were created. They have internal knowledge about themselves and their environment to reason about changes and take appropriate actions. Many approaches aiming to build such systems have been published since the start of the research area at the beginning of the 21st century. However, it is difficult to find an appropriate approach, even when all requirements of a scenario the system should be built for are known. If no suitable approach can be found, software developers have to built a new system leading to high development costs and potentially inefficient solutions due to the complexity of the system. This thesis follows two goals: (1) To make approaches building SAS more comparable through a feature model describing features of SAS, and (2) to provide a novel way of specifying SAS concisely using reference attribute grammars (RAGs) providing efficient systems. RAGs originate from the research field of compiler construction and enable the concise description of parts of the internal knowledge mentioned above as well as of the computation of the actions to cope with recognised changes. To make RAGs fully usable, this thesis presents two extensions: Relational RAGs enable the efficient handling of relations required for knowledge graphs, and Connected RAGs let RAG-based system communicate with other external systems to both recognise changes and execute actions. To evaluate the novel approaches, a classification of 30 approaches for the feature model and several case studies in the areas smart home, robotics, and system orchestration were conducted. It can be shown, that significantly less

Published
2023

37. Self-Explanation in Adaptive Systems Based on Runtime Goal-Based Models

Author

Welsh, Kris, Bencomo, Nelly, Sawyer, Pete, Whittle, Jon, Nguyen, Ngoc Thanh, Editor-in-chief, 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, and Kowalczyk, Ryszard, editor

Published
2014
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38. S-Theory: A Unified Theory of Multi-paradigm Software Development

Author

Hughes, Danny, Bencomo, Nelly, Morin, Brice, Huygens, Christophe, Shen, Zhun, Man, Ka Lok, 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, Park, James J. (Jong Hyuk), editor, Arabnia, Hamid R., editor, Kim, Cheonshik, editor, Shi, Weisong, editor, and Gil, Joon-Min, editor

Published
2013
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39. Supporting Decision-Making for Self-Adaptive Systems: From Goal Models to Dynamic Decision Networks

Author

Bencomo, Nelly, Belaggoun, Amel, 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, Doerr, Joerg, editor, and Opdahl, Andreas L., editor

Published
2013
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40. Requirements for Self-adaptation

Author

Bencomo, Nelly, 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, Lämmel, Ralf, editor, Saraiva, João, editor, and Visser, Joost, editor

Published
2013
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41. 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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42. Software Engineering Processes for Self-Adaptive Systems

Author

Andersson, Jesper, Baresi, Luciano, Bencomo, Nelly, de Lemos, Rogério, Gorla, Alessandra, Inverardi, Paola, Vogel, Thomas, 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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43. How the Web of Things Challenges Requirements Engineering

Author

Sawyer, Pete, Pathak, Animesh, Bencomo, Nelly, Issarny, Valérie, 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, Grossniklaus, Michael, editor, and Wimmer, Manuel, editor

Published
2012
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44. Relaxing Claims: Coping with Uncertainty While Evaluating Assumptions at Run Time

Author

Ramirez, Andres J., Cheng, Betty H. C., Bencomo, Nelly, Sawyer, Pete, 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, France, Robert B., editor, Kazmeier, Jürgen, editor, Breu, Ruth, editor, and Atkinson, Colin, editor

Published
2012
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45. Summary of the 5th International Workshop on Models@run.time

Author

Bencomo, Nelly, Blair, Gordon, Fleurey, Franck, Jeanneret, Cédric, 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, Dingel, Juergen, editor, and Solberg, Arnor, editor

Published
2011
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46. 4th International Workshop on Models@run.time

Author

Bencomo, Nelly, Blair, Gordon, France, Robert, Muñoz, Freddy, Jeanneret, Cédric, 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, and Ghosh, Sudipto, editor

Published
2010
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47. A Goal-Based Modeling Approach to Develop Requirements of an Adaptive System with Environmental Uncertainty

Author

Cheng, Betty H. C., Sawyer, Pete, Bencomo, Nelly, Whittle, Jon, 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, Schürr, Andy, editor, and Selic, Bran, editor

Published
2009
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48. Using Architecture Models to Support the Generation and Operation of Component-Based Adaptive Systems

Author

Bencomo, Nelly, Blair, Gordon, 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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49. Software Engineering for Self-Adaptive Systems: A Research Roadmap

Author

Cheng, Betty H. C., de Lemos, Rogério, Giese, Holger, Inverardi, Paola, Magee, Jeff, Andersson, Jesper, Becker, Basil, Bencomo, Nelly, Brun, Yuriy, Cukic, Bojan, Di Marzo Serugendo, Giovanna, Dustdar, Schahram, Finkelstein, Anthony, Gacek, Cristina, Geihs, Kurt, Grassi, Vincenzo, Karsai, Gabor, Kienle, Holger M., Kramer, Jeff, Litoiu, Marin, Malek, Sam, Mirandola, Raffaela, Müller, Hausi A., Park, Sooyong, Shaw, Mary, Tichy, Matthias, Tivoli, Massimo, Weyns, Danny, Whittle, Jon, 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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50. Third International Workshop on Models@run.time

Author

Bencomo, Nelly, Blair, Gordon, France, Robert, Muñoz, Freddy, Jeanneret, Cédric, 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, and Chaudron, Michel R. V., editor

Published
2009
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