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Perez-Palacin, DiegoORCID iD iconorcid.org/0000-0002-2736-845X
Publications (10 of 41) Show all publications
Edrisi, F., Perez-Palacin, D., Caporuscio, M. & Giussani, S. (2023). Adaptive Controllers and Digital Twin for Self-Adaptive Robotic Manipulators. In: 2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS): . Paper presented at 2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, 15-16 May 2023, Melbourne, Australia (pp. 56-67). IEEE
Open this publication in new window or tab >>Adaptive Controllers and Digital Twin for Self-Adaptive Robotic Manipulators
2023 (English)In: 2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), IEEE, 2023, p. 56-67Conference paper, Published paper (Refereed)
Abstract [en]

Robots are increasingly adopted in a wide range of unstructured and uncertain environments, where they are expected to keep quality properties such as efficiency, accuracy, and safety. To this end, robots need to be smart and continuously update their situation awareness. Self-adaptive systems pave the way for accomplishing this aim by enabling a robot to understand its surroundings and adapt to various scenarios in a systematic manner. However, some situations, e.g., adjusting adaptation rules, refining run-time models, narrowing a vast adaptation domain, and taking future scenarios into consideration, etc. may require the self-adaptive system to include additional specialized components. In this regard, this work proposes a novel approach combining the MAPE-K, adaptive controllers, and a Digital Twin of the robot to enable the managing system to be aware of new scenarios appearing at run-time and operate safely, accurately, and efficiently. A state-of-the-art robot model is employed to evaluate the suitability of the approach.

Place, publisher, year, edition, pages
IEEE, 2023
Series
ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, ISSN 2157-2305, E-ISSN 2157-2321
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-126403 (URN)10.1109/seams59076.2023.00017 (DOI)2-s2.0-85166322573 (Scopus ID)9798350311921 (ISBN)9798350311938 (ISBN)
Conference
2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, 15-16 May 2023, Melbourne, Australia
Funder
Knowledge Foundation
Available from: 2024-01-11 Created: 2024-01-11 Last updated: 2024-02-01Bibliographically approved
Grassi, V., Mirandola, R. & Perez-Palacin, D. (2023). Towards a Conceptual Characterization of Antifragile Systems. In: Proceedings - IEEE 20th International Conference on Software Architecture Companion, ICSA-C 2023: . Paper presented at 20th IEEE International Conference on Software Architecture Companion, ICSA-C 2023; Conference date: 13 March 2023 through 17 March 2023 (pp. 121-125). IEEE
Open this publication in new window or tab >>Towards a Conceptual Characterization of Antifragile Systems
2023 (English)In: Proceedings - IEEE 20th International Conference on Software Architecture Companion, ICSA-C 2023, IEEE, 2023, p. 121-125Conference paper, Published paper (Refereed)
Abstract [en]

Antifragility has recently emerged as a design principle changes during their operations. In this "New Ideas"paper we intend to support the vision that an effective application of this principle requires a clear understanding of the implications of its adoption and of its relationships with other approaches sharing a similar objective. To this end, we argue that a proper conceptual characterization of antifragility can be achieved through its inclusion within the consolidated dependability taxonomy. From this conceptual characterization we identify open architectural challenges towards the definition of a reference model for antifragile systems. © 2023 IEEE.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Antifragility, Conceptual model, Dependability, Design Principles, Reference modeling
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-123798 (URN)10.1109/ICSA-C57050.2023.00036 (DOI)2-s2.0-85159127216 (Scopus ID)9781665464598 (ISBN)
Conference
20th IEEE International Conference on Software Architecture Companion, ICSA-C 2023; Conference date: 13 March 2023 through 17 March 2023
Available from: 2023-08-17 Created: 2023-08-17 Last updated: 2023-09-07Bibliographically approved
Weyns, D., Calinescu, R., Mirandola, R., Tei, K., Acosta, M., Bennaceur, A., . . . Zisman, A. (2023). Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems. Software Engineering Notes: an Informal Newsletter of The Specia, 48(4), 20-36
Open this publication in new window or tab >>Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems
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2023 (English)In: Software Engineering Notes: an Informal Newsletter of The Specia, ISSN 0163-5948, E-ISSN 1943-5843, Vol. 48, no 4, p. 20-36Article in journal (Refereed) Published
Abstract [en]

Despite considerable research efforts on handling uncertainty in self-adaptive systems, a comprehensive understanding of the precise nature of uncertainty is still lacking. This paper summarises the findings of the 2023 Bertinoro Seminar on Uncertainty in Self- Adaptive Systems, which aimed at thoroughly investigating the notion of uncertainty, and outlining open challenges associated with its handling in self-adaptive systems. The seminar discussions were centered around five core topics: (1) agile end-toend handling of uncertainties in goal-oriented self-adaptive systems, (2) managing uncertainty risks for self-adaptive systems, (3) uncertainty propagation and interaction, (4) uncertainty in self-adaptive machine learning systems, and (5) human empowerment under uncertainty. Building on the insights from these discussions, we propose a research agenda listing key open challenges, and a possible way forward for addressing them in the coming years.

Place, publisher, year, edition, pages
ACM Publications, 2023
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-126418 (URN)10.1145/3617946.3617951 (DOI)
Available from: 2024-01-11 Created: 2024-01-11 Last updated: 2024-02-01Bibliographically approved
Bernardi, S., Gomez, A., Merseguer, J., Perez-Palacin, D. & Requeno, J. I. (2022). DICE simulation: a tool for software performance assessment at the design stage. Automated Software Engineering: An International Journal, 29, Article ID 36.
Open this publication in new window or tab >>DICE simulation: a tool for software performance assessment at the design stage
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2022 (English)In: Automated Software Engineering: An International Journal, ISSN 0928-8910, E-ISSN 1573-7535, Vol. 29, article id 36Article in journal (Refereed) Published
Abstract [en]

In recent years, we have seen many performance fiascos in the deployment of new systems, such as the US health insurance web. This paper describes the functionality and architecture, as well as success stories, of a tool that helps address these types of issues. The tool allows assessing software designs regarding quality, in particular performance and reliability. Starting from a UML design with quality annotations, the tool applies model-transformation techniques to yield analyzable models. Such models are then leveraged by the tool to compute quality metrics. Finally, quality results, over the design, are presented to the engineer, in terms of the problem domain. Hence, the tool is an asset for the software engineer to evaluate system quality through software designs. While leveraging the Eclipse platform, the tool uses UML and the MARTE, DAM and DICE profiles for the system design and the quality modeling.

Place, publisher, year, edition, pages
Springer, 2022
Keywords
Software performance, Reliability, UML, Software tool
National Category
Computer Sciences Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-111484 (URN)10.1007/s10515-022-00335-z (DOI)000773928800001 ()2-s2.0-85127228110 (Scopus ID)2022 (Local ID)2022 (Archive number)2022 (OAI)
Available from: 2022-04-20 Created: 2022-04-20 Last updated: 2023-04-06Bibliographically approved
Andersson, J., Grassi, V., Mirandola, R. & Perez-Palacin, D. (2021). A conceptual framework for resilience: fundamental definitions, strategies and metrics. Computing, 103, 559-588
Open this publication in new window or tab >>A conceptual framework for resilience: fundamental definitions, strategies and metrics
2021 (English)In: Computing, ISSN 0010-485X, E-ISSN 1436-5057, Vol. 103, p. 559-588Article in journal (Refereed) Published
Abstract [en]

The resilience system property has become more and more relevant, mainly because of the increasing dependance on a rapidly growing number of software-intensive, complex, socio-technical systems, which are facing uncertainty about changes they are expected to experience during their life-cycle and ways to deal with them. Methodologies for the systematic design and validation of resilience for such systems are thus highly necessary, and require contributions from several different fields. This paper contributes to current resilience research by providing a conceptual framework intended to serve as a common ground for the development of such methodologies. Its main points are: the identification of the main categories of changes a system should face; a clear definition of the different facets of resilience one could want to achieve, expressed in terms of the system dynamics; a mapping of each of these facets to design strategies that are better suited to achieve it; and the corresponding identification of possible metrics that can be used to assess its achievement. 

Place, publisher, year, edition, pages
Springer, 2021
Keywords
Resilience, Conceptual framework, Strategies and metrics
National Category
Computer Sciences
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-99639 (URN)10.1007/s00607-020-00874-x (DOI)000599111600001 ()2-s2.0-85097568269 (Scopus ID)2020 (Local ID)2020 (Archive number)2020 (OAI)
Projects
ALADINO
Funder
Knowledge Foundation, 20200117
Available from: 2020-12-18 Created: 2020-12-18 Last updated: 2022-04-12Bibliographically approved
Edrisi, F., Perez-Palacin, D., Caporuscio, M., Hallberg, M., Johannesson, A., Kopf, C. & Sigvardsson, J. (2021). EA Blueprint: An Architectural Pattern for Resilient Digital Twin of the Organization. In: Adler R. et al (Ed.), Dependable Computing - EDCC 2021 Workshops.: . Paper presented at DREAMS, DSOGRI, SERENE 2021, Munich, Germany, September 13, 2021 (pp. 120-131). Springer
Open this publication in new window or tab >>EA Blueprint: An Architectural Pattern for Resilient Digital Twin of the Organization
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2021 (English)In: Dependable Computing - EDCC 2021 Workshops. / [ed] Adler R. et al, Springer, 2021, p. 120-131Conference paper, Published paper (Refereed)
Abstract [en]

Advancements in Cyber-Physical Systems, IoT, Data-driven methods, and networking prepare the adequate infrastructure for constructing new organizations, where everything is connected and interact with each other. A Digital Twin of the Organization (DTO) exploits these infrastructures to provide an accurate digital representation of the organization. Beyond the usual representation of devices, machines and physical assets supplied by Digital Twins, a DTO also include processes, services, people, roles, and all other relevant elements for the operation of organizations. Therefore, DTO can play a key role in realizing and analyzing aspects of organizations, assisting managers on the knowledge of the organization status, and foreseeing possible effects of potential changes in the organization. However, due to the dynamic, open, and ever-changing environment of organizations, an established DTO will soon degrade or even lose all its utility. Therefore, a DTO needs to evolve to recover its utility when the organization changes. The development of flexible, resilient, and easy to evolve DTO has not been well-addressed yet. Most of the existing proposals are context-dependent, system-specific, or focus on providing solutions in high-level abstraction. This work leverages Enterprise Architecture to propose an architectural pattern to serve as a blueprint toward the development of resilient DTO.

Place, publisher, year, edition, pages
Springer, 2021
Series
Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937 ; 1462
Keywords
Resilient Digital Twin of Organization, Enterprise architecture, Architectural pattern
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-107110 (URN)10.1007/978-3-030-86507-8_12 (DOI)2-s2.0-85115446405 (Scopus ID)9783030865078 (ISBN)9783030865061 (ISBN)
Conference
DREAMS, DSOGRI, SERENE 2021, Munich, Germany, September 13, 2021
Available from: 2021-09-23 Created: 2021-09-23 Last updated: 2022-05-16Bibliographically approved
Bernardi, S., Famelis, M., Jézéquel, J.-M., Mirandola, R., Perez-Palacin, D., Polack, F. A. C. & Trubiani, C. (2021). Living with Uncertainty in Model-Based Development. In: Heinrich, R., Durán, F., Talcott, C., Zschaler, S. (Ed.), Composing Model-Based Analysis Tools: (pp. 159-185). Springer
Open this publication in new window or tab >>Living with Uncertainty in Model-Based Development
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2021 (English)In: Composing Model-Based Analysis Tools / [ed] Heinrich, R., Durán, F., Talcott, C., Zschaler, S., Springer, 2021, p. 159-185Chapter in book (Refereed)
Abstract [en]

Uncertainty is present in model-based developments in many different ways. In the context of composing model-based analysis tools, this chapter discusses how the combination of different models can increase or decrease the overall uncertainty. It explores how such uncertainty could be more explicitly addressed and systematically managed, with the goal of defining a conceptual framework to deal with and manage it. We proceed towards this goal both with a theoretical reasoning and a practical application through an example of designing a peer-to-peer file-sharing protocol. We distinguish two main steps: (i) software system modelling and (ii) model-based performance analysis by highlighting the challenges related to the awareness that model-based development in software engineering needs to coexist with uncertainty. This core chapter addresses Challenge 5 introduced in Chap. 3 of this book (living with uncertainty).

Place, publisher, year, edition, pages
Springer, 2021
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-127091 (URN)10.1007/978-3-030-81915-6_8 (DOI)9783030819149 (ISBN)9783030819156 (ISBN)
Available from: 2024-01-24 Created: 2024-01-24 Last updated: 2024-02-06Bibliographically approved
Caporuscio, M., Edrisi, F., Hallberg, M., Johannesson, A., Kopf, C. & Perez-Palacin, D. (2020). Architectural Concerns for Digital Twin of the Organization. In: Jansen A., Malavolta I., Muccini H., Ozkaya I., Zimmermann O. (Ed.), Software Architecture: 14th European Conference, ECSA 2020, L'Aquila, Italy, September 14–18, 2020. Paper presented at European Conference on Software Architecture, 14th European Conference, ECSA 2020, L'Aquila, Italy, September 14–18, 2020 (pp. 265-280). Springer
Open this publication in new window or tab >>Architectural Concerns for Digital Twin of the Organization
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2020 (English)In: Software Architecture: 14th European Conference, ECSA 2020, L'Aquila, Italy, September 14–18, 2020 / [ed] Jansen A., Malavolta I., Muccini H., Ozkaya I., Zimmermann O., Springer, 2020, p. 265-280Conference paper, Published paper (Refereed)
Abstract [en]

Employing a Digital Twin of the Organization would help enterprises to change and innovate, thus enhancing their organization’s sustainability. However, the lack of engineering best practices for developing and operating a Digital Twin of the Organization makes it difficult for enterprises to fully benefit from it. Many companies are currently investigating the potential use of it, but available solutions are often context-dependent or system-specific, and challenging to adapt, extend, and reuse. Therefore, digitalization is perceived as a slow, resource-demanding, and extremely expensive process whose outcome is uncertain. To this extent, enterprises seek solutions allowing them to gently introduce a Digital Twin of the Organization into their organization and to evolve it according to the changing needs and situations. This paper reports a first attempt on architecting a Digital Twin of an Organization, and discusses some architectural concerns to be addressed in order to facilitate its development and evolution.

Place, publisher, year, edition, pages
Springer, 2020
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 12292
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-98371 (URN)10.1007/978-3-030-58923-3_18 (DOI)000698737200018 ()2-s2.0-85091502566 (Scopus ID)978-3-030-58922-6 (ISBN)978-3-030-58923-3 (ISBN)
Conference
European Conference on Software Architecture, 14th European Conference, ECSA 2020, L'Aquila, Italy, September 14–18, 2020
Available from: 2020-10-07 Created: 2020-10-07 Last updated: 2022-11-03Bibliographically approved
Mahdavi-Hezavehi, S., Weyns, D., Avgeriou, P., Calinescu, R., Mirandola, R. & Perez-Palacin, D. (2020). Uncertainty in Self-adaptive Systems: A Research Community Perspective. ACM Transactions on Autonomous and Adaptive Systems, 15(4), 1-36, Article ID 10.
Open this publication in new window or tab >>Uncertainty in Self-adaptive Systems: A Research Community Perspective
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2020 (English)In: ACM Transactions on Autonomous and Adaptive Systems, ISSN 1556-4665, E-ISSN 1556-4703, Vol. 15, no 4, p. 1-36, article id 10Article in journal (Refereed) Published
Abstract [en]

One of the primary drivers for self-adaptation is ensuring that systems achieve their goals regardless of the uncertainties they face during operation. Nevertheless, the concept of uncertainty in self-adaptive systems is still insufficiently understood. Several taxonomies of uncertainty have been proposed, and a substantial body of work exists on methods to tame uncertainty. Yet, these taxonomies and methods do not fully convey the research community’s perception on what constitutes uncertainty in self-adaptive systems and on the key characteristics of the approaches needed to tackle uncertainty. To understand this perception and learn from it, we conducted a survey comprising two complementary stages in which we collected the views of 54 and 51 participants, respectively. In the first stage, we focused on current research and development, exploring how the concept of uncertainty is understood in the community and how uncertainty is currently handled in the engineering of self-adaptive systems. In the second stage, we focused on directions for future research to identify potential approaches to dealing with unanticipated changes and other open challenges in handling uncertainty in self-adaptive systems. The key findings of the first stage are: (a) an overview of uncertainty sources considered in self-adaptive systems, (b) an overview of existing methods used to tackle uncertainty in concrete applications, (c) insights into the impact of uncertainty on non-functional requirements, (d) insights into different opinions in the perception of uncertainty within the community and the need for standardised uncertainty-handling processes to facilitate uncertainty management in self-adaptive systems. The key findings of the second stage are: (a) the insight that over 70% of the participants believe that self-adaptive systems can be engineered to cope with unanticipated change, (b) a set of potential approaches for dealing with unanticipated change, (c) a set of open challenges in mitigating uncertainty in self-adaptive systems, in particular in those with safety-critical requirements. From these findings, we outline an initial reference process to manage uncertainty in self-adaptive systems. We anticipate that the insights on uncertainty obtained from the community and our proposed reference process will inspire valuable future research on self-adaptive systems.

Place, publisher, year, edition, pages
ACM Press, 2020
Keywords
Self-adaptation, uncertainty, uncertainty models, uncertainty methods, unanticipated change, uncertainty challenges, survey
National Category
Software Engineering Computer Engineering Computer Sciences
Research subject
Computer Science, Software Technology; Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-111519 (URN)10.1145/3487921 (DOI)000807171600001 ()2-s2.0-85134157537 (Scopus ID)
Projects
Trustworthy Decentralized Self-Adaptive Systems (C14/18/066)Dependable Adaptive Software Systems for the Digital World (ISPLI/18/019)UKRI EP/V026747/1 Trustworthy Autonomous Systems Node in ResilienceAssuring Autonomy Interational Programme
Available from: 2022-04-20 Created: 2022-04-20 Last updated: 2023-05-11Bibliographically approved
Calinescu, R., Mirandola, R., Perez-Palacin, D. & Weyns, D. (2020). Understanding Uncertainty in Self-adaptive Systems. In: El-Araby E.,Tomforde S.,Wood T.,Kumar P.,Raibulet C.,Petri I.,Valentini G.,Nelson P.,Porter B. (Ed.), 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2020: . Paper presented at 1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2020; Virtual, Washington; United States; 17-21 August 2020 (pp. 242-251). IEEE
Open this publication in new window or tab >>Understanding Uncertainty in Self-adaptive Systems
2020 (English)In: 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2020 / [ed] El-Araby E.,Tomforde S.,Wood T.,Kumar P.,Raibulet C.,Petri I.,Valentini G.,Nelson P.,Porter B., IEEE, 2020, p. 242-251Conference paper, Published paper (Refereed)
Abstract [en]

Ensuring that systems achieve their goals under uncertainty is a key driver for self-adaptation. Nevertheless, the concept of uncertainty in self-adaptive systems (SAS) is still insufficiently understood. Although several taxonomies of uncertainty have been proposed, taxonomies alone cannot convey the SAS research community’s perception of uncertainty. To explore and to learn from this perception, we conducted a survey focused on the SAS ability to deal with unanticipated change and to model uncertainty, and on the major challenges that limit this ability. In this paper, we analyse the responses provided by the 51 participants in our survey. The insights gained from this analysis include the view—held by 71% of our participants—that SAS can be engineered to cope with unanticipated change, e.g., through evolving their actions, synthesising new actions, or using default actions to deal with such changes. To handle uncertainties that affect SAS models, the participants recommended the use of confidence intervals and probabilities for parametric uncertainty, and the use of multiple models with model averaging or selection for structural uncertainty. Notwithstanding this positive outlook, the provision of assurances for safety-critical SAS continues to pose major challenges according to our respondents. We detail these findings in the paper, in the hope that they will inspire valuable future research on self-adaptive systems.

Place, publisher, year, edition, pages
IEEE, 2020
Keywords
Self-adaptation, uncertainty, unanticipated change, models, survey
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-99638 (URN)10.1109/ACSOS49614.2020.00047 (DOI)000719369400028 ()2-s2.0-85092714145 (Scopus ID)
Conference
1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2020; Virtual, Washington; United States; 17-21 August 2020
Available from: 2020-12-18 Created: 2020-12-18 Last updated: 2022-11-03Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2736-845X

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