| 1. |
- Weyns, Danny, et al.
(författare)
-
A Research Agenda for Smarter Cyber-Physical Systems
- 2021
-
Ingår i: Journal of Integrated Design & Process Science. - Amsterdam, Netherlands : IOS Press BV. - 1092-0617 .- 1875-8959. ; 25:2, s. 27-47
-
Tidskriftsartikel (refereegranskat)abstract
- With the advancing digitisation of society and industry we observe a progressing blending of computational, physical, and social processes. The trustworthiness and sustainability of these systems will be vital for our society. However, engineering modern computing systems is complex as they have to: i) operate in uncertain and continuously changing environments, ii) deal with huge amounts of data, and iii) require seamless interaction with human operators. To that end, we argue that both systems and the way we engineer them must become smarter. With smarter we mean that systems and engineering processes adapt and evolve themselves through a perpetual process that continuously improves their capabilities and utility to deal with the uncertainties and amounts of data they face. We highlight key engineering areas: cyber-physical systems, self-adaptation, data-driven technologies, and visual analytics, and outline key challenges in each of them. From this, we propose a research agenda for the years to come.
|
|
| 2. |
- Mahdavi-Hezavehi, Sara, et al.
(författare)
-
Uncertainty in Self-adaptive Systems : A Research Community Perspective
- 2020
-
Ingår i: ACM Transactions on Autonomous and Adaptive Systems. - : ACM Press. - 1556-4665 .- 1556-4703. ; 15:4, s. 1-36
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 3. |
- Ciccozzi, Federico, 1983-, et al.
(författare)
-
Blended modelling - What, why and how
- 2019
-
Ingår i: Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728151250 ; , s. 425-430
-
Konferensbidrag (refereegranskat)abstract
- Empirical studies indicate that user experience can significantly be improved in model-driven engineering. Blended modelling aims at mitigating this by enabling users to interact with a single model through different notations. Blended modelling contributes to various modelling qualities, including comprehensibility, analysability, and acceptability. In this paper, we define the notion of blended modelling and propose a set of dimensions that characterise blended modelling. The dimensions are grouped in two classes: user-oriented dimensions and realisation-oriented dimensions. Each dimension describes a facet that is relevant to blended modelling together with its domain (i.e., the range of values for that dimension). The dimensions offer a basic vocabulary to support tool developers with making well-informed design decisions as well as users to select appropriate tools and configure them according to the needs at hand. We illustrate how the dimensions apply to different cases relying on our experience with blended modelling. We discuss the impact of blended modelling on usability and user experience and sketch metrics to measure it. Finally, we outline a number of core research directions in this increasingly important modelling area.
|
|
| 4. |
- Shevtsov, Stepan, et al.
(författare)
-
SimCA* : A Control-theoretic Approach to Handle Uncertainty in Self-adaptive Systems with Guarantees
- 2019
-
Ingår i: ACM Transactions on Autonomous and Adaptive Systems. - : ACM Publications. - 1556-4665 .- 1556-4703. ; 13:4, s. 1-34
-
Tidskriftsartikel (refereegranskat)abstract
- Self-adaptation provides a principled way to deal with software systems' uncertainty during operation. Examples of such uncertainties are disturbances in the environment, variations in sensor readings, and changes in user requirements. As more systems with strict goals require self-adaptation, the need for formal guarantees in self-adaptive systems is becoming a high-priority concern. Designing self-adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. In general, self-adaptation covers a wide range of approaches to maintain system requirements under uncertainty, ranging from dynamic adaptation of system parameters to runtime architectural reconfiguration. Existing control-theoretic approaches have mainly focused on handling requirements in the form of setpoint values or as quantities to be optimized. Furthermore, existing research primarily focuses on handling uncertainty in the execution environment. This article presents SimCA*, which provides two contributions to the state-of-the-art in control-theoretic adaptation: (i) it supports requirements that keep a value above and below a required threshold, in addition to setpoint and optimization requirements; and (ii) it deals with uncertainty in system parameters, component interactions, system requirements, in addition to uncertainty in the environment. SimCA* provides guarantees for the three types of requirements of the system that is subject to different types of uncertainties. We evaluate SimCA* for two systems with strict requirements from different domains: an Unmanned Underwater Vehicle system used for oceanic surveillance and an Internet of Things application for monitoring a geographical area. The test results confirm that SimCA* can satisfy the three types of requirements in the presence of different types of uncertainty.
|
|
| 5. |
|
|
| 6. |
- Diniz Caldas, Ricardo, 1994, et al.
(författare)
-
Towards Mapping Control Theory and Software Engineering Properties using Specification Patterns
- 2021
-
Ingår i: 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). - Washington DC, United States : IEEE. - 9781665443937
-
Konferensbidrag (refereegranskat)abstract
- A traditional approach to realize self-adaptation in software engineering (SE) is by means of feedback loops. The goals of the system can be specified as formal properties that are verified against models of the system. On the other hand, control theory (CT) provides a well-established foundation for designing feedback loop systems and providing guarantees for essential properties, such as stability, settling time, and steady state error. Currently, it is an open question whether and how traditional SE approaches to self-adaptation consider properties from CT. Answering this question is challenging given the principle differences in representing properties in both fields. In this paper, we take a first step to answer this question. We follow a bottom up approach where we specify a control design (in Simulink) for a case inspired by Scuderia Ferrari (F1) and provide evidence for stability and safety. The design is then transferred into code (in C) that is further optimized. Next, we define properties that enable verifying whether the control properties still hold at code level. Then, we consolidate the solution by mapping the properties in both worlds using specification patterns as common language and we verify the correctness of this mapping. The mapping offers a reusable artifact to solve similar problems. Finally, we outline opportunities for future work, particularly to refine and extend the mapping and investigate how it can improve the engineering of self-adaptive systems for both SE and CT engineers.
|
|
| 7. |
- Gilson, Fabian, et al.
(författare)
-
When Natural Language Processing Jumps into Collaborative Software Engineering
- 2019
-
Ingår i: 2019 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE COMPANION (ICSA-C 2019). - : IEEE. - 9781728118765 ; , s. 238-241
-
Konferensbidrag (refereegranskat)abstract
- 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.
|
|
| 8. |
- Iftikhar, Muhammad Usman, et al.
(författare)
-
ActivFORMS : Active Formal Models for Self-adaptation
- 2014
-
Ingår i: Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. - New York, NY, USA : ACM Press. - 9781450328647 ; , s. 125-134
-
Konferensbidrag (refereegranskat)abstract
- Self-adaptation enables a software system to deal autonomously with uncertainties, such as dynamic operating conditions that are difficult to predict or changing goals. A common approach to realize self-adaptation is with a MAPE-K feedback loop that consists of four adaptation components: Monitor, Analyze, Plan, and Execute. These components share Knowledge models of the managed system, its goals and environment. To provide guarantees of the adaptation goals, state of the art approaches propose using formal models of the knowledge. However, less attention is given to the formalization of the adaptation components themselves, which is important to provide guarantees of correctness of the adaptation behavior (e.g., does the execute component execute the plan correctly?). We propose Active FORmal Models for Self-adaptation (ActivFORMS) that uses an integrated formal model of the adaptation components and knowledge models. The formal model is directly executed by a virtual machine to realize adaptation, hence active model. The contributions of ActivFORMS are: (1) the approach assures that the adaptation goals that are verified offline are guaranteed at runtime, and (2) it supports dynamic adaptation of the active model to support changing goals. We show how we have applied ActivFORMS for a small-scale robotic system
|
|
| 9. |
- Iftikhar, Muhammad Usman, et al.
(författare)
-
Assuring System Goals Under Uncertainty with Active Formal Models of Self-adaptation
- 2014
-
Ingår i: Companion Proceedings of the 36th International Conference on Software Engineering. - New York, NY, USA : ACM Publications. - 9781450327688 ; , s. 604-605
-
Konferensbidrag (refereegranskat)abstract
- Designing software systems with uncertainties, such as incomplete knowledge about changing system goals, is challenging. One approach to handle uncertainties is self-adaptation, where a system consists of a managed system and a managing system that realizes a feedback loop. The promise of self-adaptation is to enable a system to adapt itself realizing the system goals, regarding uncertainties. To realize this promise it is critical to provide assurances for the self-adaptive behaviours. Several approaches have been proposed that exploit formal methods to provide these assurances. However, an integrated approach that combines: (1) seamless integration of offline and online verification (to deal with inherent limitations of verification), with (2) support for runtime evolution of the system (to deal with new or changing goals) is lacking. In this paper, we outline a new approach named Active FORmal Models of Self-adaptation (ActivFORMS) that aims to deal with these challenges. In ActivFORMS, the formal models of the managing system are directly deployed and executed to realize self-adaptation, guaranteeing the verified properties. Having the formal models readily available at runtime paves the way for: (1) incremental verification during system execution, and (2) runtime evolution of the self-adaptive system. Experiences with a robotic system show promising results.
|
|
| 10. |
- Weyns, Danny, et al.
(författare)
-
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation
- 2022
-
Ingår i: Software Engineering Notes. - : ACM Press. - 0163-5948 .- 1943-5843. ; 47:4, s. 18-24
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)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 selfadaptation. 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.
|
|
