Tailoring complexity metrics for simulink models

Olszewska, Marta; Dajsuren, Yanja; Altinger, Harald; Serebrenik, Alexander; Waldén, Marina; Brand, Mark van den

doi:10.1145/2993412.3004853

Cited by 10 publications

(11 citation statements)

References 15 publications

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“…The objective of the work is to measure complexity so that it can be reduced to give significant impact on the lifecycle of the system. 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].…”

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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Section: Previous Workmentioning

confidence: 99%

Complexity Assessment based on UML-Activity Diagram

Lahon¹,

Sharma²

2019

IJRTE

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“…To characterize the size and complexity of the Simulink models and their organization within projects, we use a collection of standard Simulink model and complexity metrics from Olszewska et al [48]. We collect and report measurements on a model level and on a project level by aggregating the measurements from a project's models.…”

Section: Rq2: Size and Organization Of Simulink Modelsmentioning

confidence: 99%

Characteristics, potentials, and limitations of open-source Simulink projects for empirical research

et al. 2021

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Simulink is an example of a successful application of the paradigm of model-based development into industrial practice. Numerous companies create and maintain Simulink projects for modeling software-intensive embedded systems, aiming at early validation and automated code generation. However, Simulink projects are not as easily available as code-based ones, which profit from large publicly accessible open-source repositories, thus curbing empirical research. In this paper, we investigate a set of 1734 freely available Simulink models from 194 projects and analyze their suitability for empirical research. We analyze the projects considering (1) their development context, (2) their complexity in terms of size and organization within projects, and (3) their evolution over time. Our results show that there are both limitations and potentials for empirical research. On the one hand, some application domains dominate the development context, and there is a large number of models that can be considered toy examples of limited practical relevance. These often stem from an academic context, consist of only a few Simulink blocks, and are no longer (or have never been) under active development or maintenance. On the other hand, we found that a subset of the analyzed models is of considerable size and complexity. There are models comprising several thousands of blocks, some of them highly modularized by hierarchically organized Simulink subsystems. Likewise, some of the models expose an active maintenance span of several years, which indicates that they are used as primary development artifacts throughout a project’s lifecycle. According to a discussion of our results with a domain expert, many models can be considered mature enough for quality analysis purposes, and they expose characteristics that can be considered representative for industry-scale models. Thus, we are confident that a subset of the models is suitable for empirical research. More generally, using a publicly available model corpus or a dedicated subset enables researchers to replicate findings, publish subsequent studies, and use them for validation purposes. We publish our dataset for the sake of replicating our results and fostering future empirical research.

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“…Blocks and connections are the main elements of Simulink models and are counted widely [32,39]. We have included the contents of masked blocks [54] in the parent model's count.…”

Section: Number Of Blocks and Connectionsmentioning

confidence: 99%

“…Recent studies introduced measures for Simulink model modularity [15] and complexity [39], but only evaluated them on a limited number of models. In contrast we created a larger collection of 391 Simulink models.…”

Section: Related Workmentioning

confidence: 99%

Automatically finding bugs in a commercial cyber-physical system development tool chain with SLforge

Chowdhury

Soumik

Mehra

et al. 2018

Proceedings of the 40th International Conference on Software Engineering

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Cyber-physical system (CPS) development tool chains are widely used in the design, simulation, and verification of CPS data-flow models. Commercial CPS tool chains such as MathWorks' Simulink generate artifacts such as code binaries that are widely deployed in embedded systems. Hardening such tool chains by testing is crucial since formally verifying them is currently infeasible. Existing differential testing frameworks such as CyFuzz can not generate models rich in language features, partly because these tool chains do not leverage the available informal Simulink specifications. Furthermore, no study of existing Simulink models is available, which could guide CyFuzz to generate realistic models.To address these shortcomings, we created the first large collection of public Simulink models and used the collected models' properties to guide random model generation. To further guide model generation we systematically collected semi-formal Simulink specifications. In our experiments on several hundred models, the resulting SLforge generator was more effective and efficient than the state-of-the-art tool CyFuzz. SLforge also found 8 new confirmed bugs in Simulink. CCS CONCEPTS• Software and its engineering → Model-driven software engineering; Software testing and debugging; KEYWORDSCyber-physical systems, differential testing, tool chain bugs ACM Reference Format:

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Tailoring complexity metrics for simulink models

Cited by 10 publications

References 15 publications

Complexity Assessment based on UML-Activity Diagram

Complexity Assessment based on UML-Activity Diagram

Characteristics, potentials, and limitations of open-source Simulink projects for empirical research

Automatically finding bugs in a commercial cyber-physical system development tool chain with SLforge

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