ScalaMetrics

A metric analysis framework for Scala used to research multi-paradigm metrics. This framework has been developed as part of a Master's thesis.

Source code metrics are used to measure and evaluate the code quality of software projects. Metrics are available for both Object-Oriented Programming (OOP) and Functional Programming (FP). However, there is little research on source code metrics for the combination of OOP and FP. Furthermore, existing OOP and FP metrics are not always applicable. For example, the usage of mutable class variables (OOP) in lambda functions (FP) is a combination that does not occur in either paradigm on their own. Existing OOP and FP metrics are therefore unsuitable to give an indication of quality regarding these combined constructs.

Scala is a programming language which features an extensive combination of OOP and FP construct. The goal of this thesis is to research metrics for Scala which can detect potential faults when combining OOP and FP. We have implemented a framework for defining and analysing Scala metrics. Using this framework we have measured whether code was written using mostly OOP- or FP-style constructs and analysed whether this affected the occurrence of potential faults. Next, we implemented a baseline model of existing OOP and FP metrics. Candidate metrics were added to this baseline model to verify whether they improve the fault detection performance.

In the analysed projects, there was a relatively higher number of faults when mixing OOP- and FP-style code. Furthermore, most OOP metrics perform well on FP-style Scala code. The baseline model was often able to detect when code was wrong. Therefore, the candidate metrics did not significantly improve the fault detection performance of the baseline model. However, the candidate metrics did help to indicate why code contained faults. Constructs were found for which over half of the objects using those constructs contained faults.

For more info, see Github: