A general framework for measuring system complexity

Efatmaneshnik, Mahmoud; Ryan, Michael J.

doi:10.1002/cplx.21767

Cited by 37 publications

(21 citation statements)

References 43 publications

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“…In recognizing characteristics, such as emergence, nonlinear interactions and, in many cases, continuous growth of the systems, engineers found themselves dealing with the problems that [33] classified as organized complexity, entering the realm of theoretical physics. Of the 43 metrics for complexity identified by Lloyd [43], measures used in engineering are mostly model-based, that is, they refer to a model of the system to capture features such as size, regularity, and interdependencies [44]- [46].…”

Section: B Link Between Complexity Science and Engineeringmentioning

confidence: 99%

Engineering Resilient Complex Systems: The Necessary Shift Toward Complexity Science

Punzo

Tewari

Butans

et al. 2020

IEEE Systems Journal

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This position article addresses resilience in complex engineering and engineered systems (CES). It offers a synthesis of academic thinking with an empirical analysis of the challenge. This article puts forward argumentations and a conceptual framework in support of a new understanding of CES resilience as the product of continuous learning in between disruptive events. CES are in continuous evolution and with each generation they become more complex as they adapt to their environment. While this evolution takes place, new failure modes arise with the engineering of their resilience having to evolve in parallel to cope with them. Our position supports the role of an overarching complexity science framework to investigate the resilience of CES, including their temporal evolution, resilience features, the management and decision layers, and the transparency of boundaries between interconnected systems. The conclusion identifies the value of a complexity perspective to address CES resilience. Extending the latest understanding of resilience, we propose a circular framework where features of CES are related to a resilience event and complexity science explains the importance of interconnections with external systems, the increasingly fast system evolution and the stratification of heterogeneous layers.

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Section: B Link Between Complexity Science and Engineeringmentioning

confidence: 99%

Engineering Resilient Complex Systems: The Necessary Shift Toward Complexity Science

Punzo

Tewari

Butans

et al. 2020

IEEE Systems Journal

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“…The importance of complexity measure in the early stages have been seen in other works stating that complexity measure is an early indicator of the effort required for testing, implementing quality factors and minimising cost [22,23,24]. The presence of subjective component in complexity analysis is also considered to be a significant aspect which requires to be addressed while measuring system complexity [25]. The proposed approach considers the activity diagram from UML diagrams to capture the process view of the architecture.…”

Section: Previous Workmentioning

confidence: 99%

Complexity Assessment based on UML-Activity Diagram

Lahon¹,

Sharma²

2019

IJRTE

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Assessing complexity can significantly contribute to the attainment of the various quality attributes associated with a system. The avoidable complexity can be identified and reduced on the basis of the assessment. It holds the key to success of the system being developed. Various evaluation methods exist which have specific objectives and basis and all contribute to enhance product quality. In this paper a Complexity Assessment approach based on Activity Diagrams (CAAD) is proposed to evaluate the process view of the architecture of a system. The proposed approach estimates the complexity of the system/class/function from the UML representation of the process view of the architecture in the form of activity diagrams. This complexity measure may be used to assess and estimate the time and effort required to develop the system. This approach can estimate the coding complexity in terms of size without actually developing the code for the system/class/function. The paper is on calculating a complexity factor C from the given activity diagram and further develop a relationship between C and LOC metrics.

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“…Given its complexity (i.e., procedures and interactions among its subsystems) and even if the definition of complexity is not always clear (Efatmaneshnik and Ryan, 2016), to examine a railway system in its entirety poses considerable difficulties. Willcox et al (2011) agreed on defining the complexity as the ability of the system to produce unexpected states, drifting from the design phase.…”

Section: Introductionmentioning

confidence: 99%

Wheel maintenance in rolling stock: safety challenges in the defect detection process

Chatzimichailidou

Martinetti

Majumdar³

et al. 2018

IJSSE

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The proper and timely maintenance of railway rolling stock is essential for the safety of railway operations. Inaccurate inspection can lead to inadequate repair of defects and to great safety challenges in respect to the entire railway system. The detection and repair of any defect, such as cracks, in the wheels prior to a failure can significantly reduce train derailments and improved operational performance. This paper examines the wheel maintenance process in maintenance depots in the Netherlands on the basis of literature review, observations and interviews. First, it highlights various detection methods, including the risks of the incorrect detection of a flawed wheel profile. This paper introduces a flowchart as a concise illustration of the maintenance process; that is, both the detection and treatment of defects. With this in hand, the authors, as well as anyone involved in maintenance, are able to identify the points where the process is vulnerable and may be prone to incidents/accidents. Based on this procedure, improvements to the current wheel maintenance process can be proposed. The method that the flowchart is based on is also presented herein, along with the findings obtained throughout its steps.

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A general framework for measuring system complexity

Cited by 37 publications

References 43 publications

Engineering Resilient Complex Systems: The Necessary Shift Toward Complexity Science

Engineering Resilient Complex Systems: The Necessary Shift Toward Complexity Science

Complexity Assessment based on UML-Activity Diagram

Wheel maintenance in rolling stock: safety challenges in the defect detection process

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