Comparing the applicability of complexity measurements for simulink models during integration testing: an industrial case study
Paper in proceedings, 2015

Context: Simulink models are used during software integration testing in the automotive domain on hardware in the loop (HIL) rigs. As the amount of software in cars is increasing continuously, the number of Simulink models for control logic and plant models is growing at the same time. Objective: The study aims for investigating the applicability of three approaches for evaluating model complexity in an industrial setting. Additionally, insights on the understanding of maintainability in industry are gathered. Method: Simulink models from two vehicle projects at a German premium car manufacturer are evaluated by applying the following three approaches: Assessing a model's (a) size, (b) structure, and (c) signal routing. Afterwards, an interview study is conducted followed by an on-site workshop in order to validate the findings. Results: The measurements of 65 models resulted in comparable data for the three measurement approaches. Together with the interview studies, conclusions were drawn on how well each approach reflects the experts' opinions. Additionally, it was possible to get insights on maintainability in an industrial setting. Conclusion: By analyzing the results, differences between the three measurement approaches were revealed. The interviews showed that the expert opinion tends to favor the results of the simple size measurements over the measurement including the signal routing.

complexity

hardware in the loop

Simulink

maintainability

metrics

software validity

interview study

integration testing

Author

Jan Schroeder

University of Gothenburg

Christian Berger

University of Gothenburg

T. Herpel

University of Gothenburg

Miroslaw Staron

University of Gothenburg

Proceedings of the Second International Workshop on Software Architecture and Metrics, SAM '15

35-40

Subject Categories

Software Engineering

DOI

10.1109/SAM.2015.12

ISBN

978-1-4673-7076-9

More information

Created

10/10/2017