  Several important aspects of software product quality can be evaluated using
dynamic metrics that effectively capture and reflect the software's true
runtime behavior. While the extent of research in this field is still
relatively limited, particularly when compared to research on static metrics,
the field is growing, given the inherent advantages of dynamic metrics. The aim
of this work is to systematically investigate the body of research on dynamic
software metrics to identify issues associated with their selection, design and
implementation. Mapping studies are being increasingly used in software
engineering to characterize an emerging body of research and to identify gaps
in the field under investigation. In this study we identified and evaluated 60
works based on a set of defined selection criteria. These studies were further
classified and analyzed to identify their relativity to future dynamic metrics
research. The classification was based on three different facets: research
focus, research type and contribution type. We found a strong body of research
related to dynamic coupling and cohesion metrics, with most works also
addressing the abstract notion of software complexity. Specific opportunities
for future work relate to a much broader range of quality dimensions.
