Identifying Metrics' Biases When Measuring or Approximating Size in Heterogeneous Languages.
Paper i proceeding, 2015

To compare the effectiveness of development techniques, the size of compared software systems needs to be taken into account. However, in industry new development techniques often come with changes in the applied programming languages. Goal: Our goal is to investigate how different size metrics and approximations are biased towards the languages c and c++. Further, we investigate whether triangulation of metrics has the potential to compensate for biases. Method: We identify crucial preconditions for a triangulation and investigate on 34 open source projects, whether a set of 16 size metrics fulfills these preconditions for the languages c and c++. Results: We identify how metrics differ in their biases and find that the preconditions for triangulation are fulfilled. Conclusion: Triangulation has the potential to address language biases, but high variance among metrics and tools need to be taken into account, too.


Regina Hebig

Sorbonne Université

Jesper Derehag

Ericsson AB

Michel Chaudron

Göteborgs universitet

Empirical Software Engineering and Measurement (ESEM 2015), ACM/IEEE International Symposium on.

1949-3789 (eISSN)

978-1-4673-7899-4 (ISBN)







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