A Systematic Mapping Study on Dynamic Metrics and Software Quality

TL;DR

This systematic mapping study reviews 60 research works on dynamic software metrics, highlighting their focus on coupling, cohesion, and complexity, and identifying future opportunities across diverse quality dimensions.

Contribution

The paper provides a comprehensive classification and analysis of existing research on dynamic metrics, revealing research trends, gaps, and future directions in the field.

Findings

Strong focus on dynamic coupling and cohesion metrics

Most studies address software complexity

Identified opportunities for broader quality dimension research

Abstract

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.