“What should I work on next?” Code metrics can help you answer that question. They can single out sections of your code that are likely to contain bugs. They can help you get a toehold on a legacy system that’s poorly covered by tests.
In this session, we’ll talk about the properties of source code that give us a lot of information for little effort: complexity, test coverage, churn, and so on. We’ll discuss ways to obtain these metrics for popular programming languages. We’ll also talk about what to do when you need ad hoc measurements for a specific project.
Attendees will end up with an understanding of how to apply metrics to their own source code and, equally importantly, how not to apply them.
Ian Dees saw his first Timex Sinclair 1000 over 20 years ago, and was instantly hooked. Since then, he’s debugged embedded assembly code using an oscilloscope, written desktop apps in C++, and joyfully employed scripting languages to make testing less painful. Ian currently writes GUI code for test instruments as a Software Engineer at Tektronix.
Ian is author of the Pragmatic titles Scripted GUI Testing With Ruby and Using JRuby.
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