Digital Transformation
Test-driven development
Who or what do you trust? Think about your relationship with people or products and tell us: do you trust someone or something you have no experience with? Speaking more specifically about products: do you trust them before performing basic tests? Put another way: would you buy a car if, when you turned the key or pressed the button, it didn't start?
As obvious as the above questions may sound, they lead us to an obvious conclusion: we trust a product, service, or even a brand after they have been minimally tested. That is why testing is so important in industry, including software: it tells you whether or not you can trust the system you use.
In general, trust is directly linked to the fulfillment of our expectations. We have already discussed here on the blog how valuable automation is. Thanks to it, we can make something work in the future that we could only imagine before. If we imagine the same thing about a product or service, if we assume that it will work as we expect, our expectations are met. Consequently, we will believe that it is of high quality.
This is precisely why testing is the primary tool for Quality Engineering in the software industry. Thanks to testing, we can trust a system and feel confident in using it.
From proof of concept to approval testing, every stage of system development undergoes rounds and rounds of testing. And as applications become more complex, with the adoption of new architectures and technologies, the amount of testing increases exponentially.
To make it easier to understand how testing works in an application development project, let's divide it into two main groups. The first is "who" performs the tests. The second is "what" is tested.
Tests are performed by two types of "actors": humans or robots. Manual tests are performed by people, usually a QA analyst – short for quality assurance. When tests are automated, robots do the work. They are a type of system whose function is to perform steps that repeatedly test the logic and rules of the application under development. Obviously, nowadays, there are already artificial intelligence agents designed to perform automated tests.
The "what" group being tested can also be divided into two: the parts and the relationship between them. In unit tests, we check the functioning of pieces of the system, often very small parts: one or a few functions, a logic flow. The goal here is to isolate blocks of the application to see if they work as expected separately.
Once each part has been checked, integration tests are performed: we combine several blocks of the application and test them as a group. To try to make the image clearer, think of a matryoshka doll: first you test the dimensions and functioning of each one, and then you test whether they fit together to form a single toy. For it to work as expected, each doll must fit perfectly into the other.
As we have already mentioned, testing is involved in every stage of system creation. These procedures are so fundamental that there are development methods geared towards them, such as the traditional TDD (Test-Driven Development) and its "evolution," BDD (Behavior-Driven Development).
As we have already mentioned, with applications becoming more complex, other testing methodologies and techniques have emerged. One that is widely used is contract testing, which is fundamental for microservices. In this scope of verification, the interaction between the various microservices used to make the entire application work is tested.
Not only are the rules and features of the application tested, but other aspects also need to function as expected to ensure its quality. One very important aspect is availability, the guarantee that it will work whenever needed.
One approach to testing the availability of an application is chaos engineering. It was designed to migrate an extremely complex system, that of Netflix. In 2010, the company decided to transfer its streaming service to the AWS infrastructure, an operation that could severely affect its customers' experience. To ensure a smooth migration and guarantee the quality of the experience for its users, the Netflix team created the "Chaos Monkey," a program that purposely and randomly shut down part of its infrastructure, "forcing chaos" and, consequently, testing the resilience and availability of its system.
These and other contemporary testing methodologies are among Inmetrics' main specialties: through QAOps practices, we eliminate the boundaries between testing, development, and operations to increase deployment speed, strengthen your business, reduce time to market, and ensure the highest possible ROI. It is no wonder that we are a leading company in Continuous Testing in ISG Provider Lens™ Next-Gen ADM Services Brazil 2022.
If your company's operations are growing in volume and complexity and you want to ensure the quality control of your applications in an integrated manner, click here and contact us! Our team is ready to accelerate your transformation, ensuring quality at every stage of your journey.
