  Fault-proneness is a measure that indicates the possibility of programming
errors occurring within a software system. On the other hand, change-proneness
refers to the potential for modifications to be made to the software. Both of
these measures are crucial indicators of software maintainability, as they
influence internal software metrics such as size, inheritance, and coupling,
particularly when numerous changes are made to the system. In the literature,
research has predicted change- and fault-proneness using internal software
metrics that is almost a decade old. However, given the continuous evolution of
software systems, it is essential to revisit and update our understanding of
these relationships. Therefore, we have conducted an empirical study to revisit
the relationship between internal software metrics and change-proneness, and
faultproneness, aiming to provide current and relevant insights. In our study,
we identified 25 internal software metrics along with the measures of
change-proneness and fault-proneness within the wellknown open-source systems
from the Apache and Eclipse ecosystems. We then analyzed the relationships
between these metrics using statistical correlation methods. Our results
revealed that most of the metrics have little to no correlation with
fault-proneness. However, metrics related to inheritance, coupling, and
comments showed a moderate to high correlation with change-proneness. These
findings will assist developers to minimize the higher correlated software
metrics to enhance maintainability in terms of change- and fault-proneness.
Additionally, these insights can guide researchers in developing new approaches
for predicting changes and faults by incorporating the metrics that have been
shown to have stronger correlations.
