Complexity Challenges in Development of Cyber-Physical Systems

Törngren, Martin; Sellgren, Ulf

doi:10.1007/978-3-319-95246-8_27

Cited by 59 publications

(58 citation statements)

References 30 publications

(39 reference statements)

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“…Thus, the resource demands for testing systems in this domain is dramatically higher compared to non-CPS-based applications. Adaptive approaches focusing on performance while keeping high levels of coverage might improve the level of testability of CPS [64,65].…”

Section: Trade-off Between Coverage and Performancementioning

confidence: 99%

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

Grano

Laaber

Panichella

et al. 2021

IIEEE Trans. Software Eng.

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Automated test case generation is an effective technique to yield high-coverage test suites. While the majority of research effort has been devoted to satisfying coverage criteria, a recent trend emerged towards optimizing other non-coverage aspects. In this regard, runtime and memory usage are two essential dimensions: less expensive tests reduce the resource demands for the generation process and for later regression testing phases. This study shows that performance-aware test case generation requires solving two main challenges: providing accurate measurements of resource usage with minimal overhead and avoiding detrimental effects on both final coverage and fault detection effectiveness. To tackle these challenges we conceived a set of performance proxies (inspired by previous work on performance testing) that provide an approximation of the test execution costs (i.e., runtime and memory usage). Thus, we propose an adaptive strategy, called pDynaMOSA, which leverages these proxies by extending DynaMOSA, a state-of-the-art evolutionary algorithm in unit testing. Our empirical study -involving 110 non-trivial Java classes-reveals that our adaptive approach has comparable results to DynaMOSA over seven different coverage criteria (including branch, line, and weak mutation coverage) and similar fault detection effectiveness (measured via strong mutation coverage). Additionally, we observe statistically significant improvements regarding runtime and memory usage for test suites with a similar level of target coverage. Our quantitative and qualitative analyses highlight that our adaptive approach facilitates selecting better test inputs, which is an essential factor to test production code with fewer resources.

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Section: Trade-off Between Coverage and Performancementioning

confidence: 99%

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

Grano

Laaber

Panichella

et al. 2021

IIEEE Trans. Software Eng.

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“…The full potential can only be obtained when new engineering methodologies are in place to ensure future CPS are sufficiently safe, secure, available and cost-efficient. In addressing these questions, our paper draws upon recent investigations of CPS complexity [6,10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Interactions between software and the electronics platforms and reuse of legacy components (sometimes black-box or poorly documented/understood), further contribute to complexity. Interactions between components in computer systems include both local and global interactions and exhibit much faster characteristic timescales compared to physical interactions [10].…”

mentioning

confidence: 99%

“…Combining cyber and physical components enables feedback and adaptive systems, providing cost-efficient capabilities otherwise impossible but also characterized by more complex behaviors (e.g., hybrid real-time systems) including a multitude of possible faults and failure modes. As a particular characteristic, a CPS will be characterized by a multiplicity of interfaces and interrelations that encompass both explicit and implicit dependencies among CPS components, and between the CPS and its environment [10]. Correspondingly, a change in one part of a system may affect many others, producing unexpected or undesired side effects from the close coupling and tight integration.…”

mentioning

confidence: 99%

“…This results in a situation where the properties are generally difficult to trade-off explicitly and predict during design. It is striking that several of the U.S. definitions of CPS emphasize co-design of cyber and physical parts and the importance of multi-disciplinarity because CPS requires "integration" and composition across a number of aspects and layers (see e.g., [3,10,40]).…”

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confidence: 99%

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How to Deal with the Complexity of Future Cyber-Physical Systems?

Törngren

Grogan

2018

Designs

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Cyber-Physical Systems (CPS) integrate computation, networking and physical processes to produce products that are autonomous, intelligent, connected and collaborative. Resulting Cyber-Physical Systems of Systems (CPSoS) have unprecedented capabilities but also unprecedented corresponding technological complexity. This paper aims to improve understanding, awareness and methods to deal with the increasing complexity by calling for the establishment of new foundations, knowledge and methodologies. We describe causes and effects of complexity, both in general and specific to CPS, consider the evolution of complexity, and identify limitations of current methodologies and organizations for dealing with future CPS. The lack of a systematic treatment of uncertain complex environments and "composability", i.e., to integrate components of a CPS without negative side effects, represent overarching limitations of existing methodologies. Dealing with future CPSoS requires: (i) increased awareness of complexity, its impact and best practices for how to deal with it, (ii) research to establish new knowledge, methods and tools for CPS engineering, and (iii) research into organizational approaches and processes to adopt new methodologies and permit efficient collaboration within and across large teams of humans supported by increasingly automated computer aided engineering systems.Designs 2018, 2, 40 2 of 16 A CPS is thus characterized by an integration of computing and physical elements, typically including feedback loops, into various networks with both physical and cyber interfaces. We consider human-CPS to be a special (but common) category of CPS where humans are integral elements of the system together with technical parts. Figure 1 illustrates interactions between cyber (C), physical (P) and human (H) elements as well as information and physical interactions between the corresponding components. CPS are developed, produced, used and maintained by teams of people (H) and supporting tools, including computer aided engineering software (C) and hardware-in-the-loop simulation ((C) and (P))). We refer to these (people and tools) as Collaborative Information Processing Systems (CIPS). Finally, both CPS and CIPS act in specific environments. For example, the CPS environment may be a factory in which an automated vehicle operates and the CIPS environment includes related stakeholders such as component suppliers as well as applicable legislation and engineering guidelines/standards.

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DLR Institute of Systems Engineering for Future Mobility – Technical Trustworthiness as a Basis for Highly Automated and Autonomous Systems

Bolles¹,

Hagemann²,

Hahn³

et al. 2022

INSIGHT

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The newly established Institute of Systems Engineering for Future Mobility within the German Aerospace Center opened its doors at the beginning of 2022. Emerging from the former OFFIS Division Transportation after a two‐year transition phase, the new institute can draw on more than thirty years of experience in the research field of safety‐critical systems. With the transition to the DLR, the institute's new research roadmap focuses on technical trustworthiness for highly automated and autonomous systems. Within this field, the institute will develop new concepts, methods, and tools to support the integration and assurance of technical trustworthiness for automated and autonomous systems during their whole lifecycle – from the early development through verification, validation, and operation to updates of the systems in the field.

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Complexity Challenges in Development of Cyber-Physical Systems

Cited by 59 publications

References 30 publications

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

How to Deal with the Complexity of Future Cyber-Physical Systems?

DLR Institute of Systems Engineering for Future Mobility – Technical Trustworthiness as a Basis for Highly Automated and Autonomous Systems

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