An application without data is like a car without fuel. Much like a mechanical engine needs gasoline to get anywhere at all, software needs data to achieve a determined objective. Much like you need fuel to test drive a car, you need data to test run an application.
This is the realm of managing test metrics and data, which can be broadly defined as the manner in which QA teams go about generating and discovering test data, and subsequently using it in order to test the functionality of an application. In an agile or DevOps continuous deployment and testing model, test data management can be a somewhat challenging task. Nevertheless, it's a central component of QA management, and it's one that can be helped along by adhering to the following three best practices.
Often, an organization will refer to the use of already existing databases that serve as repositories for information that is relevant to the application in production. In an agile environment, the data in use could be from actual users that have already interfaced with the app. This is standard practice for generating and discovering the test data that will be used to execute test cases during QA management. It should almost go without saying that this test data must in no way risk compromising personally identifiable information, or put an organization's sensitive information at risk. As such, names, addresses, contact information, and other such details should be wiped clean so that they cannot be used for malicious purposes.
That having been said, it's still important that the test data in use is as close to simulating the real thing as possible. According to Software Testing Help, this is absolutely necessary for ensuring that the test cases accurately portray what will happen when the app is live.
"Test data plays a key role in identifying where a product or feature can completely break," Software Testing Help wrote. "Always have a practice of polling and validating the kind of data fed to the test environment in different phases of testing."
Refresh Your Data
Much as it makes sense to reuse test cases whenever possible, test data is often relevant for more than one test cycle. The reason this is so important is that it can save a lot of time in generating and discovering new test data.
Interestingly, the best way to go about achieving this is the same way that an agile test management tool handles test cases—by logging them into a centrally accessible, shared repository. Not only does this make it easy to keep all of your test data in one place, but it also makes it easy to alter the store by adding to it, or by removing data that is no longer relevant.
Again, this is important because it ensures that time-sensitive data is up to date, and that reusable data does not have to be recreated. It also ensures that irrelevant data is not wasting storage space and therefore money.
Automation Is Your Friend
Just as regression testing and other repetitive test cases can be automated, so too can the production of test data. According to Software Specialist contributor Scott Poliziani, this is useful for several reasons, such as the ability to "replicate large amounts of traffic and usage through an application that would not otherwise be feasible." As a general rule, Poliziani recommends automating anything that makes sense to automate. This is because automation can save a substantial amount of time in the long run.
Another test data management process that can be automated is the refreshing of data.
"This would help in exposing any errors that may occur with respect to data during testing," Software Testing Help wrote. "A possible way to do this is by comparing the results that are produced by a set of data from consecutive test runs. Next, automate this process of comparing."
Combined with the aforementioned central repository and safety protocols, your QA team will be in a strong position to streamline its test data management efforts.