Early Validation of Automation Plant Control Software using Simulation Based on Assumption Modeling and Validation Use Cases

Brandstetter, Veronika; Froese, Andreas; Tenbergen, Bastian; Vogelsang, Andreas; Wehrstedt, Jan Christoph; Weyer, Thorsten

doi:10.7250/csimq.2015-4.04

Cited by 6 publications

(7 citation statements)

References 19 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The potential that interviewees in Company A see for early simulation of requirements aligns well with related work by Brandstetter et al [9] and Vogelsang et al [53], both of which highlight the feasibility of such an approach. In contrast, existing frameworks that propose formalisation on all abstraction levels (e.g.…”

Section: Rq2: Potential Of Models In Resupporting

confidence: 84%

“…Apart from the SPES framework, there exist several proposed processes and frameworks for requirements modelling, e.g. [6,9,10,17,53].…”

mentioning

confidence: 99%

“…Brandstetter et al [9] present a process to perform early validation of requirements by means of simulation, using the control software of a desalination plant as an industrial case. Assumptions and properties of the system are captured in context models.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Use, potential, and showstoppers of models in automotive requirements engineering

2018

View full text Add to dashboard Cite

Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g. to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g. restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multidisciplinary environments. Additionally, we see the need for future work in the area of model use, i.e. information extraction from models by non-expert modellers.

show abstract

Section: Rq2: Potential Of Models In Resupporting

confidence: 84%

“…Apart from the SPES framework, there exist several proposed processes and frameworks for requirements modelling, e.g. [6,9,10,17,53].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Use, potential, and showstoppers of models in automotive requirements engineering

2018

View full text Add to dashboard Cite

show abstract

“…Our work is intended to primarily foster the manual validation of the functional adequacy of a system during early stages of development. This work complements our previous work on using diagrammatic representation to validate stakeholder intentions [57][58][59], safety properties [24,60,61], and context assumptions [62].…”

Section: Modeling During Validation and Verificationmentioning

confidence: 56%

Multi-Level Message Sequence Charts to Validate the Collaborative Automotive Cyber-Physical Systems

Daun¹,

Tenbergen²,

Brings³

et al. 2021

JASEN

Self Cite

View full text Add to dashboard Cite

Autonomous driving and e-mobility are swiftly becoming not only the work of science fiction or popular science, but a reality.A key focus of manufacturers and suppliers in the automotive domain is of course to specify systems that implement this reality. Often, scenarios at type-level are used throughout the development process to specify system behavior and interaction within the car, as scenario models are comparatively easy to understand and can easily be subjected to manual validation. However, autonomous driving and e-mobility require interaction not just of systems within the same car, but collaboration between multiple cars as well as between cars and miscellaneous road infrastructure (e.g., smart road signs). The car becomes a Cyber-Physical System that dynamically forms collaborating networks at runtime with other Cyber-Physical System to create functionality that goes beyond the scope of the individual vehicle (e.g., resolve a traffic jam). Consequently, a plethora of possible compositions of such a network exist and must be specified and validated completely to assure their adequate and safe execution at runtime. Doing this at type-level with scenario models becomes prohibitively tedious, error prone, and likely results in unrealistic development cost. To combat this issue, we investigate the use of multi-level Message Sequence Charts to allow for specifying interaction scenarios between collaborative Cyber-Physical System in a network of collaborating automotive Cyber-Physical System. To assist the developer in systematically defining multi-level Message Sequence Charts, we propose two processes. The resulting diagrams use a mixture of type and instance-level abstractions within one conceptual diagram. This allows reducing the required effort to manually validate the adequacy of scenarios to a manageable amount because information within the scenarios can be validated in batches. At the same time, instance-level defects become more obvious. Evaluation results from a controlled experiment show that multi-level Message Sequence Charts contribute to effectiveness and efficiency of manual validation for collaborative automotive Cyber-Physical System.

show abstract

“…We have successfully applied functional operational context diagrams to depict collaborative networks for CPS. Specifically, we have shown an involved runtime interaction between smart ACCs resolving a traffic jam in Tenbergen et al 59 We have also successfully applied functional operational context diagrams to validate the control logic of desalination plants against process requirements in Brandstetter et al 86 …”

Section: Notation and Examplesmentioning

confidence: 99%

Context modeling for cyber‐physical systems

Daun

Tenbergen

2022

J Software Evolu Process

View full text Add to dashboard Cite

When developing cyber-physical systems (CPS), the context is of vital importance.CPS interact with the world not only through sensing the environment and acting upon it (like embedded systems) but also by communicating with other CPS (like systems in the Internet of Things [IoT]). This means that the context interactions CPS must deal with are much greater than regular embedded or IoT systems: On the one hand, external systems and human users constrain the specific interaction among them. On the other hand, properties of these external systems, human users, and laws, regulations, or standards constrain the way the CPS must be developed. In this paper, we propose a comprehensive, ontologically grounded context modeling framework to systematically explore the problem space in which a CPS under development will operate. This allows for the systematic elicitation of requirements for the CPS, early validation and verification of its properties, and safety assessment of its context interactions at runtime.

show abstract

Early Validation of Automation Plant Control Software using Simulation Based on Assumption Modeling and Validation Use Cases

Cited by 6 publications

References 19 publications

Use, potential, and showstoppers of models in automotive requirements engineering

Use, potential, and showstoppers of models in automotive requirements engineering

Multi-Level Message Sequence Charts to Validate the Collaborative Automotive Cyber-Physical Systems

Context modeling for cyber‐physical systems

Contact Info

Product

Resources

About