View all web browser and mobile devices available in our cloud-based test lab.
It is no secret that test data is vital to dev teams; it is the lifeblood of conducting realistic tests to best prepare your apps for production. Every test requires data, and every test environment requires test data in its setup. Test data goes a long way in helping create and execute more comprehensive and realistic test scenarios, feed mock services, and cover testing in early stages of development — which ultimately all lead to higher quality applications.
But when it comes to mobile testing, leveraging mobile application data has not always been easy to glean actionable next steps. Teams often experience inefficiencies, bottlenecks and dependencies, less-than-stellar test coverage, and test data inconsistencies. It is enough to make devs want to pull their hair out in frustration.
Rest assured, though, there is a simple solution. Pairing Perfecto with BlazeMeter’s test data capabilities as complementary forces powers up your testing to unlock time savings, higher quality and more efficient tests, and data consistency across the board. This blog will explore the common testing challenges associated with mobile application data and the various ways you can benefit from using synthetic test data in your mobile testing.
For a long time, test data has often hindered the development process as much as it is intended to help it. There are a few reasons bumping up against test data can be cumbersome:
Test data is difficult to prepare. Setting up the test environment and keeping the integrity of things like relationships of the data and referential integrity are not simple tasks.
Test data cannot be taken “as is” from production. There are security and legal issues that prevent the use of PII data.
Inputting “dummy” data does not work. It is not as simple as entering “Jane Doe” for names or “555-555-5555" for phone numbers. Mobile application data needs to be robust and have a variety of scenarios to simulate as realistically as possible.
While data masking is a helpful technique to create a version of data that looks structurally similar yet hides sensitive information, it may not an ideal technique. It may be suitable for a known use case, but it is not suitable for new functionalities. It also adds an extra step in getting test data from production environments which, of course, adds more time.
What do all those mobile application data management challenges add up to?
In a word? Headaches. Specifically, though, they add up to team inefficiencies because manual test data creation is error-prone and time-consuming. Bottlenecks and dependencies develop when testers rely on other items to identify test data and make it available for testing. There is a lack of test coverage when production data that has been masked only offers test coverage for known use cases and cannot account for new functionalities. Finally, there are test data inconsistencies abound due to modern business applications containing multiple data stores that need to be kept in sync.
Sure, those are a lot of hoops to jump through when dealing with mobile application data. But there is a way to overcome those challenges. A few ways, actually:
Generate PII-Free Data. Using PII or production data is a big compliance no-no. Data masking can be a solution, but it becomes an arduous task through cooperation and work from Database Administrators (DBAs). It is not their main job or priority, so they will treat your request as such. Some larger organizations may have a specialized team that manages mobile application test data, but that occurrence is rare.
While masking data is a common industry practice and meets compliance with GDPR and other regulations, BlazeMeter offers a nimbler approach to building data — from scratch. Even when the data is needed fast and, on the fly, BlazeMeter Test Data allows Perfecto users to generate their own PII-free data for mobile testing.
Generate Missing Data. Throughout the dev cycle, sometimes test data is needed but is not yet complete. For example, let’s say you are testing your mobile app and need inputs of New Jersey addresses. If you don’t readily have them, BlazeMeter Test Data can generate them for you.
Additionally, testers may need specific data to conduct edge testing. If you are testing a use case where a mobile subscription expiries on a certain date (and causes premium features to disappear), you will want to test dates closely before and after the expiration date to ensure you are getting the functionality you want.
Generate Negative Testing Data. Have you ever wondered what happens when you input wrong or faulty data in your testing? It is far from a guarantee that your test will be robust enough to give the appropriate response. Think, for instance, if a feature of your app is location-based. Someone types in “Wisconsin” in a form field that is asking for Birth Date — what happens then?
BlazeMeter Test Data can generate “incorrect” data or data in the wrong format to test against that very scenario. Humans are flawed so your testing should be flawless. More than a few of Perfecto’s customers have reported more than 80% of their testing consists of negative testing use cases.
Asking yourself how one goes about doing all that? We are glad you asked. The answer to all your headache-inducing questions is right there in front of you (we mean this quite literally).
Pairing Perfecto’s seamless, end-to-end testing platform with BlazeMeter test data allows you to generate and leverage high quality, synthetic test data for your mobile app testing—all via a simple API. For the first time, you can look all those mobile testing challenges in the face and laugh — nothing can stop you now! With a robust testing platform and unmatched test data generation capabilities, you will be well on your way to a stellar application.
If anything you have just read applies to you — if you have been nodding along thinking, “Yes! Yes, I need this!” — then check out the premier pairing of Perfecto and BlazeMeter in action with a demo.