61 research outputs found
Comparing Static and Dynamic Weighted Software Coupling Metrics
Coupling metrics that count the number of inter-module connections in a software system
are an established way to measure internal software quality with respect to modularity. In addition to
static metrics, which are obtained from the source or compiled code of a program, dynamic metrics
use runtime data gathered, e.g., by monitoring a system in production. Dynamic metrics have been
used to improve the accuracy of static metrics for object-oriented software. We study weighted
dynamic coupling that takes into account how often a connection (e.g., a method call) is executed
during a systemâs run. We investigate the correlation between dynamic weighted metrics and their
static counterparts. To compare the different metrics, we use data collected from four different
experiments, each monitoring production use of a commercial software system over a period of four
weeks. We observe an unexpected level of correlation between the static and the weighted dynamic
case as well as revealing differences between class- and package-level analyses
The relevance of model-driven engineering thirty years from now
International audienceAlthough model-driven engineering (MDE) is now an established approach for developing complex software systems, it has not been universally adopted by the software industry. In order to better understand the reasons for this, as well as to identify future opportunities for MDE, we carried out a week-long design thinking experiment with 15 MDE experts. Participants were facilitated to identify the biggest problems with current MDE technologies, to identify grand challenges for society in the near future, and to identify ways that MDE could help to address these challenges. The outcome is a reflection of the current strengths of MDE, an outlook of the most pressing challenges for society at large over the next three decades, and an analysis of key future MDE research opportunities
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