The Challenges of Building Advanced Mechatronic Systems

Schäfer, Wilhelm; Wehrheim, Heike

doi:10.1109/fose.2007.28

Cited by 84 publications

(44 citation statements)

References 33 publications

(27 reference statements)

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“…The heterogeneous and complex nature of mechatronic systems pose different challenges for testing [10]. In particular, automated mechatronic testing infrastructures must be able to support the following requirements.…”

Section: A Mechatronic Systems Testing Requirementsmentioning

confidence: 99%

An Integrated Model-Driven Approach for Mechatronic Systems Testing

Filho

Budnik

2012

2012 IEEE Fifth International Conference on Software Testing, Verification and Validation

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Abstract-Mechatronic systems integrate mechanical, electrical and software subsystems. They are increasingly important in mission-critical infrastructures in different domains including automotive, healthcare, energy and transportation sectors. As such, the adequate testing and validation of such infrastructures are of prime importance. Mechatronic systems testing has been supported by different isolated industrial and research approaches including automated test infrastructures, model-based testing, and test execution engines. While these approaches have individual benefits, they are usually applied in isolation, suffering from different weaknesses. This paper reports on an integrated model-driven approach for mechatronic systems testing, where existing approaches are combined and enhanced. The result is unprecedented levels of automation and testability. We discuss the design and implementation of our approach, illustrating its use with a hybrid calculator example.

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Section: A Mechatronic Systems Testing Requirementsmentioning

confidence: 99%

An Integrated Model-Driven Approach for Mechatronic Systems Testing

Filho

Budnik

2012

2012 IEEE Fifth International Conference on Software Testing, Verification and Validation

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“…This wide spectrum of system types, adaptation concerns, and dynamic goals has made it difficult to develop general runtime V&V methods. Unsurprisingly, V&V of SAS systems running in safety-critical environments is particularly challenging [7].…”

Section: Introductionmentioning

confidence: 99%

Towards Practical Runtime Verification and Validation of Self-Adaptive Software Systems

Tamura

Villegas

Müller

et al. 2013

Software Engineering for Self-Adaptive Systems II

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Abstract. Software validation and verification (V&V) ensures that software products satisfy user requirements and meet their expected quality attributes throughout their lifecycle. While high levels of adaptation and autonomy provide new ways for software systems to operate in highly dynamic environments, developing certifiable V&V methods for guaranteeing the achievement of self-adaptive software goals is one of the major challenges facing the entire research field. In this chapter we (i) analyze fundamental challenges and concerns for the development of V&V methods and techniques that provide certifiable trust in self-adaptive and self-managing systems; and (ii) present a proposal for including V&V operations explicitly in feedback loops for ensuring the achievement of software self-adaptation goals. Both of these contributions provide valuable starting points for V&V researchers to help advance this field.

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“…However, the models used in individual engineering disciplines and their best-practice tools often require a range of terms and/or modeling structures to describe a given common concept leading to semantically heterogeneous models [15]. Unfortunately, most engineering tools assume homogeneous data models, where concepts with similar meaning include syntactically similar encoding.…”

Section: Introductionmentioning

confidence: 99%

Engineering project management using the Engineering Cockpit: A collaboration platform for project managers and engineers

Moser¹,

Mordinyi²,

Winkler³

et al. 2011

2011 9th IEEE International Conference on Industrial Informatics

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Abstract-Automation Systems Engineering projects typically depend on contributions from several engineering disciplines. While available software tools are strong in supporting each individual engineering discipline, there is very little work on engineering process management and monitoring across multidiscipline engineering projects. In this paper, we present the Engineering Cockpit, a social-network-style collaboration platform for automation system engineering project managers and engineers, which provides a role-specific single entry point for project monitoring, collaboration, and management. We present a prototype implementation of the Engineering Cockpit and discuss its benefits and limitations based on the feedback of our industry partners. Major results are that the Engineering Cockpit increases the team-awareness of engineers and provides projectspecific information across engineering discipline boundaries.

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The Challenges of Building Advanced Mechatronic Systems

Cited by 84 publications

References 33 publications

An Integrated Model-Driven Approach for Mechatronic Systems Testing

An Integrated Model-Driven Approach for Mechatronic Systems Testing

Towards Practical Runtime Verification and Validation of Self-Adaptive Software Systems

Engineering project management using the Engineering Cockpit: A collaboration platform for project managers and engineers

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