Testing (Introduction to Statistical Computing)
Three-Toed Sloth 2013-09-19
Summary:
Lecture 7: Our code implements a method for solving problems we expect to encounter in the future; but why should we trust those solutions? We establish the reliability of the code by testing it. To respect the interfaces of the code, we test the substance of the answers, not the procedure used to obtain them, even though it is the reliability of the procedure we ultimate care about. We test both for the actual answer in particular cases and by cross-checking different uses of the same code which should lead to the same answer. Because we do not allow our tests to give us any false alarms, their power to detect errors is limited, and must be focused at particular kinds of errors. We make a virtue of necessity by using a diverse battery of tests, and shaping the tests so that they tell us where errors arise. The testing-programming cycle alternates between writing code and testing its correctness, adding new tests as new errors are discovered. The logical extreme of this is test-driven development, where tests represent the specification of the software's behavior in terms of practical consequences. Drawbacks of testing. Some pointers to more advanced tools for writing, maintaining and using tests in R.
(Why yes, this lecture was something of a lay sermon on epistemology.)