Why Pay to Measure Code?
With so many software tools and utilities that will provide
line of code metrics, why would anyone purchase a tool? The
answer for CodeMeasure is easy and should help you decide
if it is right for you and your organization. The two reasons
to select CodeMeasure are: consistency of results and language
And now the free trial version of CodeMeasure allows you
to run an analysis for free. You can view, capture, and print
the CLOC graph. You'll need to purchase a license to save
the results to a spreadsheet file.
Consistency of Results
An important part of taking software development metrics
is consistency. The first step toward consistency when measuring
code is to measure the same way every time. CodeMeasure is
uniquely designed to measure the evolution of software across
multiple versions and not just a simple comparison of two
versions that is typical. Running all your comparisons at
the same time ensures you get a consistent measurement across
versions without taking valuable engineering time building
an environment to consistently measure 2 versions at a time
and compiling results. Another unique advantage CodeMeasure
offers, results from its language independence, allowing the
same tool to measure Java development, PHP scripting, C, C++,
or any line-based language and delivering consistent metrics
on all your language-based development projects.
Language independence seems counter intuitive to the concept
of accurately measuring software evolution because everyone
knows that all lines of code aren't created equal. Similarly,
all languages aren't the same, so the effort required for
a line of PHP is different than the effort for a line of C++.
The problem isn't with the metric, but with the analysis.
If information on changed lines of code for the evolution
of the Apache server (developed in C++) is compared with the
same changed lines of code information for Ptolemy (developed
in Java) does it tell me which language is better? Of course
not, applying the same metric to two unrelated things doesn't
lead to an accurate conclusion. The bottom line is having
a standard set of metrics helps provide context and makes
it easier to present an understandable analysis of development