Correlations of software code metrics: An empirical study
Paper in proceedings, 2017

Background: The increasing up-trend of software size brings about challenges related to release planning and maintainability. Foreseeing the growth of software metrics can assist in taking proactive decisions regarding different areas where software metrics play vital roles. For example, source code metrics are used to automatically calculate technical debt related to code quality which may indicate how maintainable a software is. Thus, predicting such metrics can give us an indication of technical debt in the future releases of software. Objective: Estimation or prediction of software metrics can be performed more meaningfully if the relationships between different domains of metrics and relationships between the metrics and different domains are well understood. To understand such relationships, this empirical study has collected 25 metrics classified into four domains from 9572 software revisions of 20 open source projects from 8 well-known companies. Results: We found software size related metrics are most correlated among themselves and with metrics from other domains. Complexity and documentation related metrics are more correlated with size metrics than themselves. Metrics in the duplications domain are observed to be more correlated to themselves on a domain-level. However, a metric to domain level relationship exploration reveals that metrics with most strong correlations are in fact connected to size metrics. The Overall correlation ranking of duplication metrics are least among all domains and metrics. Contribution: Knowledge earned from this research will help to understand inherent relationships between metrics and domains. This knowledge together with metric-level relationships will allow building better predictive models for software code metrics.

Software Code Metrics

Correlation of Metrics

Spearman’s Rank Correlation

Software Engineering

Author

Md Abdullah Al Mamun

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Christian Berger

University of Gothenburg

Jörgen Hansson

University of Skövde

27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement, IWSM Mensura 2017; Gothenburg; Sweden; 25 October 2017 through 27 October 2017

255-266

Areas of Advance

Information and Communication Technology

Subject Categories

Computer and Information Science

Software Engineering

DOI

10.1145/3143434.3143445

ISBN

978-1-4503-4853-9

More information

Latest update

3/5/2018 1