Simulink models are also software

Abstract

In automotive industry, more and more complex electronics and software systems are being developed to enable the innovation and to decrease costs. Besides the complex multimedia, comfort, and safety systems of conventional vehicles, automotive companies are required to develop more and more complex engine, aftertreatment, and energy management systems for their (hybrid) electric vehicles to reduce fuel consumption and harmful emissions. MATLAB/Simulink is one of the most popular graphical modeling languages and a simulation tool for validating and testing control software systems. Due to the increasing complexity and size of Simulink models of automotive software systems, it has become a necessity to maintain the Simulink models.In this paper, we defined metrics for assessing the modularity of Simulink models. A Java tool developed to measure the defined metrics on Simulink models interfaces with a visualization tool to facilitate the maintenance tasks of the Simulink models. The modularity metrics is furthermore validated in two phases. In the first phase, the modularity measurement is validated against the experts evaluation of a system. In the second phase, we studied the relationship between metric values and number of faults. We have observed that high coupling metric values frequently correspond to number of faults. Modularity metrics will be extended to architectural quality metrics for automotive systems.

On negative results when using sentiment analysis tools for software engineering research

“…However, if different conclusions are derived for the same dataset when different sentiment analysis tools are used, then we can conclude that the disagreement between sentiment analysis tools affects validity of conclusions in the software engineering domain. Recent studies considering sentiment in software engineering data tend to include additional variables, e.g., sentiment analysis has been recently combined with politeness analysis (Danescu-Niculescu-Mizil et al 2013) to study issue resolution time (Destefanis et al 2016;. To illustrate the impact of the choice of sentiment analysis tool on the study outcome in presence of other analysis techniques, we repeat the response time study but combine sentiment analysis with politeness analysis.…”

“…Furthermore, presence of machine-generated text, e.g., error messages, stack traces or source code, might have affected our results. Similarly, to reduce the threats related to the choice of the statistical machinery we opt for the T-approach (Konietschke et al 2012) that has been successfully applied in the software engineering context (Dajsuren et al 2013;Li et al 2014;Sun et al 2015;Vasilescu et al 2013;Vasilescu et al 2013;Wang et al 2014;Yu et al 2016). …”

Tailoring complexity metrics for simulink models

“…It is an extension of the tool that measures modularity metrics of Simulink models [11]. The complexity analysis tool reads Simulink MDL files with the standard structural format and generates the metrics files with the list of subsystems and the respective complexity metrics.…”

“…We used the data collected from the second automotive application consisting of 40 subsystems, from which half of the subsystems contain defects because of proprietary library subsystems. Since there are a number of tied values and we aim to establish if any complexity metric and the number of faults are statistically correlated rather than measuring the degree of the linear relationship between variables, we use the Kendall's τ correlation test as used in our modularity assessment of Simulink models [11].…”

How healthy are software engineering conferences?

“…A more comprehensive discussion of T goes beyond the scope of this article and can be found in [36]. Small examples detailing the application of T can be found in [21,36] and additional scientific applications of the technique in [37][38][39].…”