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Calinescu, R., Weyns, D., Gerasimou, S. & Habli, I. (2019). Architecting Trustworthy Self-adaptive Systems (Tutorial). In: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019): . Paper presented at IEEE International Conference on Software Architecture (ICSA-C), Hamburg, GERMANY, MAR 25-29, 2019 (pp. 3-4). IEEE
Open this publication in new window or tab >>Architecting Trustworthy Self-adaptive Systems (Tutorial)
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019), IEEE, 2019, p. 3-4Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2019
National Category
Software Engineering Information Systems
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-86997 (URN)10.1109/ICSA-C.2019.00008 (DOI)000474737700002 ()2-s2.0-85066472491 (Scopus ID)978-1-7281-1876-5 (ISBN)
Conference
IEEE International Conference on Software Architecture (ICSA-C), Hamburg, GERMANY, MAR 25-29, 2019
Available from: 2019-07-26 Created: 2019-07-26 Last updated: 2019-08-29Bibliographically approved
Gilson, F. & Weyns, D. (2019). When Natural Language Processing Jumps into Collaborative Software Engineering. In: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019): . Paper presented at IEEE International Conference on Software Architecture (ICSA-C), Hamburg, GERMANY, MAR 25-29, 2019 (pp. 238-241). IEEE
Open this publication in new window or tab >>When Natural Language Processing Jumps into Collaborative Software Engineering
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019), IEEE, 2019, p. 238-241Conference paper, Published paper (Refereed)
Abstract [en]

Software engineering is an intrinsically collaborative activity, especially in the era of Agile Software Development. Many actors are partaking in development activities, such that a common understanding should be reached at numerous stages during the overall development life-cycle. For a few years now, Natural Language Processing techniques have been employed either to extract key information from free-form text or to generate models from the analysis of text in order to ease the sharing of knowledge across all parties. A significant part of these approaches focuses on retrieving lost domain and architectural knowledge through the analysis of documents, issue management systems or other forms of knowledge management systems. However, these post-processing methods are time-consuming by nature since they require to invest significant resources into the validation of the extracted knowledge. In this paper, inspired by collaborative tools, bots and Natural Language extraction approaches, we envision new ways to collaboratively record and document design decisions as they are discussed. These decisions will be documented as they are taken and, for some of them, static or behavioural models may be generated on-the-fly. Such an interactive process will ensure everyone agrees on critical design aspects of the software. We believe development teams will benefit from this approach because manual encoding of design knowledge will be reduced and will not be pushed to a later stage, when not forgotten.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
agile software development, documentation, model-driven development, natural language processing
National Category
Software Engineering Language Technology (Computational Linguistics)
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-86998 (URN)10.1109/ICSA-C.2019.00049 (DOI)000474737700043 ()2-s2.0-85066474736 (Scopus ID)978-1-7281-1876-5 (ISBN)
Conference
IEEE International Conference on Software Architecture (ICSA-C), Hamburg, GERMANY, MAR 25-29, 2019
Available from: 2019-07-26 Created: 2019-07-26 Last updated: 2019-08-29Bibliographically approved
Berrevoets, R. & Weyns, D. (2018). A QoS-aware Adaptive Mobility Handling Approach for LoRa-based IoT Systems. In: 2018 12TH IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2018): . Paper presented at 12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), SEP 03-07, 2018, Trento, ITALY (pp. 130-139). IEEE
Open this publication in new window or tab >>A QoS-aware Adaptive Mobility Handling Approach for LoRa-based IoT Systems
2018 (English)In: 2018 12TH IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2018), IEEE, 2018, p. 130-139Conference paper, Published paper (Refereed)
Abstract [en]

Internet-of-Things (IoT) is an emergent paradigm that is increasingly applied in smart cities. A popular technology used in IoT is LoRa that supports long-range wireless communication. In this research, we study LoRa-based IoT systems with battery-powered end nodes that collect and communicate data to a gateway for further processing. Existing approaches in such IoT systems usually only consider stationary end nodes. We focus on systems with mobile end nodes, paving the way to new applications such as target tracking. Key Quality of Service (QoS) requirements for these settings are the reliability of the communication and energy consumption. With mobile end nodes, ensuring these QoS is challenging as the system is subject to continuous changes. In this paper, we investigate how the settings of a mobile end node impact key performance indicators for reliability and energy consumption. Based on insights obtained from extensive field experiments, we devise an algorithm that automatically adapts the settings of a mobile end node to ensure its QoS requirements for a setup with a single gateway. We then extend the algorithm to a setup with multiple gateways. We demonstrate how the algorithms achieve the QoS requirements of a mobile end node in a concrete IoT deployment.

Place, publisher, year, edition, pages
IEEE, 2018
Series
International Conference on Self-Adaptive and Self-Organizing Systems, ISSN 1949-3673
National Category
Computer and Information Sciences Signal Processing
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-81105 (URN)10.1109/SASO.2018.00024 (DOI)000459885200014 ()2-s2.0-85061896468 (Scopus ID)978-1-5386-5172-8 (ISBN)
Conference
12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), SEP 03-07, 2018, Trento, ITALY
Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-08-29Bibliographically approved
Rabiser, R., Schmid, K., Becker, M., Botterweck, G., Galster, M., Groher, I. & Weyns, D. (2018). A study and comparison of industrial vs. Academic software product line research published at SPLC. In: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1: . Paper presented at 22nd International Systems and Software Product Line Conference, SPLC 2018, 10-14 September 2018, Gothenburg, Sweden (pp. 14-24). ACM Publications
Open this publication in new window or tab >>A study and comparison of industrial vs. Academic software product line research published at SPLC
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2018 (English)In: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1, ACM Publications, 2018, p. 14-24Conference paper, Published paper (Refereed)
Abstract [en]

The study presented in this paper aims to provide evidence for the hypothesis that software product line research has been changing and that the works in industry and academia have diverged over time.We analysed a subset (140) of all (593) papers published at the Software Product Line Conference (SPLC) until 2017. The subset was randomly selected to cover all years as well as types of papers. We assessed the research type of the papers (academic or industry), the kind of evaluation (application example, empirical, etc.), and the application domain. Also, we assessed which product line life-cycle phases, development practices, and topics the papers address. We present an analysis of the topics covered by academic vs. Industry research and discuss the evolution of these topics and their relation over the years. We also discuss implications for researchers and practitioners. We conclude that even though several topics have received more attention than others, academic and industry research on software product lines are actually rather in line with each other. © 2018 Association for Computing Machinery.

Place, publisher, year, edition, pages
ACM Publications, 2018
Series
ACM International Conference Proceeding Series
Keywords
Academia, Industry, Software product lines, SPLC, Computer software, Software design, Application examples, Development practices, Industry research, Product-lines, Software Product Line, Life cycle
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-83807 (URN)10.1145/3233027.3233028 (DOI)2-s2.0-85055511291 (Scopus ID)9781450363716 (ISBN)9781450364645 (ISBN)
Conference
22nd International Systems and Software Product Line Conference, SPLC 2018, 10-14 September 2018, Gothenburg, Sweden
Available from: 2019-05-28 Created: 2019-05-28 Last updated: 2019-06-03Bibliographically approved
Weyns, D., Iftikhar, M. U., Hughes, D. & Matthys, N. (2018). Applying architecture-based adaptation to automate the management of internet-of-things. In: Carlos E. Cuesta, David Garlan Jennifer Pérez (Ed.), 12th European Conference on Software Architecture, ECSA 2018: . Paper presented at 12th European Conference on Software Architecture, ECSA 2018, Madrid, Spain, September 24–28, 2018 (pp. 449-467). Springer
Open this publication in new window or tab >>Applying architecture-based adaptation to automate the management of internet-of-things
2018 (English)In: 12th European Conference on Software Architecture, ECSA 2018 / [ed] Carlos E. Cuesta, David Garlan Jennifer Pérez, Springer, 2018, p. 449-467Conference paper, Published paper (Refereed)
Abstract [en]

Architecture-based adaptation equips a software-intensive system with a feedback loop that enables the system to adapt itself at runtime to changes to maintain its required quality goals. To guarantee the required goals, existing adaptation approaches apply exhaustive verification techniques at runtime. However these approaches are restricted to small-scale settings, which often limits their applicability in practice. To tackle this problem, we introduce an innovative architecture-based adaptation approach to solve a concrete practical problem of VersaSense: automating the management of Internet-of-Things (IoT). The approach, called MARTAS, equips a software system with a feedback loop that employs Models At Run Time and Statistical techniques to reason about the system and adapt it to ensure the required goals. We apply MARTAS to a building security case system, which is a representative IoT system deployed by VersaSense. The application comprises a set of IoT devices that communicate sensor data over a time synchronized smart mess network to a central monitoring facility. We demonstrate how MARTAS outperforms a conservative approach that is typically applied in practice and a state-of-the-art adaptation approach for different quality goals, and we report lessons learned from this industrial case. © Springer Nature Switzerland AG 2018.

Place, publisher, year, edition, pages
Springer, 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11048
Keywords
Architecture-based adaptation, Automated management, Feedback loop, Internet-of-Things, Self-adaptation, Feedback, Network architecture, Software architecture, Architecture based adaptation, Conservative approaches, Feed-back loop, Internet of Things (IOT), Self adaptation, Software intensive systems, Verification techniques, Internet of things
National Category
Interaction Technologies
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-83572 (URN)10.1007/978-3-030-00761-4_4 (DOI)000476935800004 ()2-s2.0-85057266777 (Scopus ID)9783030007607 (ISBN)
Conference
12th European Conference on Software Architecture, ECSA 2018, Madrid, Spain, September 24–28, 2018
Available from: 2019-05-27 Created: 2019-05-27 Last updated: 2019-08-28Bibliographically approved
Weyns, D., Ericsson, M., Löwe, W., Frejdestedt, F., Thornadtsson, J. & Hulth, A.-K. (2018). Applying Self-Adaptation to Automate the Management of Online Documentation of Telecom Systems. In: 14th International Conference on Automation Science and Engineering (CASE): Munich, Germany, August 20-24, 2018. Paper presented at 14th International Conference on Automation Science and Engineering (CASE), Munich, Germany, August 20-24, 2018 (pp. 1375-1380). IEEE
Open this publication in new window or tab >>Applying Self-Adaptation to Automate the Management of Online Documentation of Telecom Systems
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2018 (English)In: 14th International Conference on Automation Science and Engineering (CASE): Munich, Germany, August 20-24, 2018, IEEE, 2018, p. 1375-1380Conference paper, Published paper (Refereed)
Abstract [en]

Engineering software-intensive systems, such as production systems, is complex as these systems are subject to various types of changes that are often difficult to anticipate before deployment. Tackling this complexity requires joint expertise from different backgrounds. In this paper we focus on the problem of maintaining online technical documentation of telecom systems. In the context of continuous deployment and ever-changing user needs, high quality of the documentation of such products is in a key concern of users. To tackle this problem, different experts worked together equipping the online documentation system with a feedback loop. This feedback loop tracks changes in the system and its context and automatically adapts the documentation accordingly. The results demonstrate that this self-adaptation approach offers a viable solution to tackle the maintainability problem of online documentation of telecom systems.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-80973 (URN)10.1109/COASE.2018.8560502 (DOI)978-1-5386-3593-3 (ISBN)
Conference
14th International Conference on Automation Science and Engineering (CASE), Munich, Germany, August 20-24, 2018
Funder
Knowledge Foundation, 20150088
Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-03-14Bibliographically approved
Shevtsov, S., Berekmeri, M., Weyns, D. & Maggio, M. (2018). Control-Theoretical Software Adaptation: A Systematic Literature Review. IEEE Transactions on Software Engineering, 44(8), 784-810
Open this publication in new window or tab >>Control-Theoretical Software Adaptation: A Systematic Literature Review
2018 (English)In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 44, no 8, p. 784-810Article in journal (Refereed) Published
Abstract [en]

Modern software applications are subject to uncertain operating conditions, such as dynamics in the availability of services and variations of system goals. Consequently, runtime changes cannot be ignored, but often cannot be predicted at design time. Control theory has been identified as a principled way of addressing runtime changes and it has been applied successfully to modify the structure and behavior of software applications. Most of the times, however, the adaptation targeted the resources that the software has available for execution (CPU, storage, etc.) more than the software application itself. This paper investigates the research efforts that have been conducted to make software adaptable by modifying the software rather than the resource allocated to its execution. This paper aims to identify: the focus of research on control-theoretical software adaptation; how software is modeled and what control mechanisms are used to adapt software; what software qualities and controller guarantees are considered. To that end, we performed a systematic literature review in which we extracted data from 42 primary studies selected from 1512 papers that resulted from an automatic search. The results of our investigation show that even though the behavior of software is considered non-linear, research efforts use linear models to represent it, with some success. Also, the control strategies that are most often considered are classic control, mostly in the form of Proportional and Integral controllers, and Model Predictive Control. The paper also discusses sensing and actuating strategies that are prominent for software adaptation and the (often neglected) proof of formal properties. Finally, we distill open challenges for control-theoretical software adaptation.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
self-adaptive software, control theory, software adaptation
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-69336 (URN)10.1109/TSE.2017.2704579 (DOI)000441791100004 ()2-s2.0-85052241956 (Scopus ID)
Available from: 2017-12-16 Created: 2017-12-16 Last updated: 2019-08-29Bibliographically approved
Van der Donckt, M. J., Weyns, D., Iftikhar, M. U. & Singh, R. K. (2018). Cost-Benefit Analysis at Runtime for Self-adaptive Systems Applied to an Internet of Things Application. In: Damiani, E Spanoudakis, G Maciaszek, L (Ed.), Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering: . Paper presented at 13th International Conference on Evaluation of Novel Approaches to Software Engineering, Funchal, PORTUGAL, MAR 23-24, 2018 (pp. 478-490). SciTePress
Open this publication in new window or tab >>Cost-Benefit Analysis at Runtime for Self-adaptive Systems Applied to an Internet of Things Application
2018 (English)In: Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering / [ed] Damiani, E Spanoudakis, G Maciaszek, L, SciTePress, 2018, p. 478-490Conference paper, Published paper (Refereed)
Abstract [en]

Ensuring the qualities of modern software systems, such as the Internet of Things, is challenging due to various uncertainties, such as dynamics in availability of resources or changes in the environment. Self-adaptation is an established approach to deal with such uncertainties. Self-adaptation equips a software system with a feedback loop that tracks changes and adapts the system accordingly to ensure its quality goals. Current research in this area has primarily focussed on the benefits that self-adaptation can offer. However, realising adaption can also incur costs. Ignoring these costs may invalidate the expected benefits. We start with demonstrating that the costs for adaptation can be significant. To that end, we apply a state-of-the-art approach for self-adaptation to an Internet of Things (IoT) application. We then present CB@R (Cost-Benefit analysis @ Runtime), a novel model-based approach for runtime decision-making in self-adaptive systems. CB@R is inspired by the Cost-Benefit Analysis Method (CBAM), which is an established approach for analysing costs and benefits of architectural decisions. We evaluate CB@R for a real world deployed IoT application and compare it with the conservative approach applied in practice and a state-of-the-art self-adaptation approach.

Place, publisher, year, edition, pages
SciTePress, 2018
Keywords
Self-adaptation, MAPE, Models at Runtime, Statistical Model Checking, Cost-Benefit Analysis Method, CBAM, Internet-of-Things, IoT
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-79104 (URN)10.5220/0006815404780490 (DOI)000450506700050 ()2-s2.0-85052335988 (Scopus ID)978-989-758-300-1 (ISBN)
Conference
13th International Conference on Evaluation of Novel Approaches to Software Engineering, Funchal, PORTUGAL, MAR 23-24, 2018
Available from: 2018-12-06 Created: 2018-12-06 Last updated: 2019-05-28Bibliographically approved
Weyns, D. (2018). Engineering self-adaptive software systems - An organized tour. In: Proceedings - 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018: . Paper presented at 3rd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018, 3 September 2018 through 7 September 2018 (pp. 1-2). IEEE
Open this publication in new window or tab >>Engineering self-adaptive software systems - An organized tour
2018 (English)In: Proceedings - 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018, IEEE, 2018, p. 1-2Conference paper, Published paper (Refereed)
Abstract [en]

Engineering software that is subject to uncertainties that are difficult to anticipate before deployment is challenging. Self-adaptation extends a software system with an external feedback loop system that monitors the system and adapts its configuration or architecture to ensure that its qualities are met under uncertain operating conditions. In this tutorial, we provide a particular perspective on the evolution of the field of selfadaptation in six waves. These waves put complementary aspects of engineering self-adaptive systems in focus that synergetically have contributed to the current body of knowledge in the field.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Adaptive systems, Computer software, Body of knowledge, Engineering software, Feed-back loop, Operating condition, Self adaptation, Self-adaptive software systems, Self-adaptive system, Software systems, Monitoring
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
urn:nbn:se:lnu:diva-82748 (URN)10.1109/FAS-W.2018.00012 (DOI)000469065900001 ()2-s2.0-85061545355 (Scopus ID)9781538651759 (ISBN)
Conference
3rd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2018, 3 September 2018 through 7 September 2018
Available from: 2019-05-27 Created: 2019-05-27 Last updated: 2019-06-13Bibliographically approved
Calinescu, R., Weyns, D., Gerasimou, S., Iftikhar, M. U., Habli, I. & Kelly, T. (2018). Engineering Trustworthy Self-Adaptive Software with Dynamic Assurance Cases. IEEE Transactions on Software Engineering, 44(11), 1039-1069
Open this publication in new window or tab >>Engineering Trustworthy Self-Adaptive Software with Dynamic Assurance Cases
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2018 (English)In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 44, no 11, p. 1039-1069Article in journal (Refereed) Published
Abstract [en]

Building on concepts drawn from control theory, self-adaptive software handles environmental and internal uncertainties by dynamically adjusting its architecture and parameters in response to events such as workload changes and component failures. Self-adaptive software is increasingly expected to meet strict functional and non-functional requirements in applications from areas as diverse as manufacturing, healthcare and finance. To address this need, we introduce a methodology for the systematic ENgineering of TRUstworthy Self-adaptive sofTware (ENTRUST). ENTRUST uses a combination of (1) design-time and runtime modelling and verification, and (2) industry-adopted assurance processes to develop trustworthy self-adaptive software and assurance cases arguing the suitability of the software for its intended application. To evaluate the effectiveness of our methodology, we present a tool-supported instance of ENTRUST and its use to develop proof-of-concept self-adaptive software for embedded and service-based systems from the oceanic monitoring and e-finance domains, respectively. The experimental results show that ENTRUST can be used to engineer self-adaptive software systems in different application domains and to generate dynamic assurance cases for these systems.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Self-adaptive software systems, software engineering methodology, assurance evidence, assurance cases
National Category
Software Engineering
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-67353 (URN)10.1109/TSE.2017.2738640 (DOI)000449964600002 ()2-s2.0-85029184307 (Scopus ID)
Available from: 2017-08-22 Created: 2017-08-22 Last updated: 2019-08-29Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1162-0817

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