What Is Random Testing?

Random testing is a practice many software developers use to test their work. It's also known as "test-driven development" or "test-first programming." This practice relies on the idea that you should randomly choose your test cases. It means that the tests are not written in the order in which your program would be used but in random order. The idea behind this is that by writing the test cases randomly, you'll be able to catch bugs that would otherwise go unnoticed if you had written them in a different order. Random testing is black box testing in which developers enter random inputs into the system to check the results. One typical example is using random digits to test a software function that returns results based on those integers. These functions include "for loops" or other algorithms for delivering an effect, where a set of random test cases simulates or approximates a broader set of circumstances entered by theoretical users. For example, suppose you have a program that calculates the average number of widgets produced per hour by each employee. The program inputs the number of hours worked (integer), the number of widgets produced (integer), and an integer representing employee identification. It then outputs an integer representing the hourly production rate for each employee in terms of devices produced per hour. To test this program using random input, you could run it with various values for hours worked and see what output it makes for each value. You would also want to run it with multiple values for widget production and see what result it has for each weight. Random testing is a pretty contentious topic. Some developers and experts use the term to refer to inefficient or incompetent testing, where directed testing is seen as a superior method. Others argue that because automated systems instead of human professionals can do it, random testing can be more efficient regarding how much testing is needed. However, you look at it, one thing's for sure random testing is not always what it seems.