Bugs in software is a very common problem, code reviews can help to catch
bugs early on and detect which code is the most complex and may introduce
bugs but when the code base is very large it can be costly to review all the
code. Cyclomatic complexity can be used to give an indication of how complex
the system source code is and help the developers to select which code they
should review. But when measuring cyclomatic complexity on code written
according to the functional paradigm, McCabe’s formula will not be sufficient
since it is a formula most suitable for imperative code. Therefore we are
making adaptations to a formula suited for pure functional languages in order
to fit functional JavaScript. We are using an inductive empirical quantitative
measurement method to calculate cyclomatic complexity on a directed graph
implementation in order to define adaptations for functional JavaScript. Our
results show a working adapted version of the formula. We have measured on
a graph implemented in Haskell and on a corresponding functional JavaScript
version which results in a cyclomatic complexity difference at only 0.375.