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When most firms employed a waterfall development model, it was widely joked about in the industry that Google kept its products in beta forever. Google has been a pioneer in making the case for in-production testing. Traditionally, before a build could go live, a tester was responsible for testing all scenarios, both defined and extempore, in a testing environment. However, this concept is evolving on multiple fronts today. For example, the tester is no longer testing alone. Developers, designers, build engineers, other stakeholders, and end users, both inside and outside the product team, are testing the product and providing feedback.

Smartphones have changed the way humans interact with technology. Be it travel, fitness, lifestyle, video games, or even services, it’s all just a few touches away (quite literally so). We only need to look at the growing throngs of smartphone or tablet users vs. desktop users to grasp this reality.

Unit and functional testing are the prime ways of verifying the JavaScript code quality. However, a host of tools are available that can also check code before or during its execution in order to test its quality and adherence to coding standards. With each tool having its unique features and advantages contributing to its testing capabilities, you can use the tool that best suits your need for performing JavaScript testing.

It’s strange to hear someone declare, “This can’t be tested.” In reply, I contend that everything can be tested. However, one must be pleased with the outcome of testing, which might include failure, financial loss, or personal injury. Could anything be tested when a claim is made with this understanding?

In some sense, testing can be more difficult than coding, as validating the efficiency of the test cases (i.e., the ‘goodness’ of your tests) can be much harder than validating code correctness. In practice, the tests are just executed without any validation beyond the pass/fail verdict. On the contrary, the code is (hopefully) always validated by testing. By designing and executing the test cases the result is that some tests have passed, and some others have failed. Testers do not know much about how many bugs remain in the code, nor about their bug-revealing efficiency.