Software testing has evolved from an inconvenient ad-hoc process to an integral part of the software development lifecycle. However, while many teams have caught on to the benefits of test automation frameworks, some organizations have yet to scale up and expand their test coverage with cloud-based devices for integration tests.
Let’s take a look at the role of test automation in software development, some of the most popular frameworks, and how BitBar can help you expand test coverage and scale your integration tests.
What is Test Automation?
Software tests have grown from an ad-hoc pre-deployment routine to an integrated part of the development and DevOps processes. Instead of manually testing critical workflows or functionality, test automation has made it possible to build a library of tests that run before each major deployment to ensure that recent changes didn’t break anything.
Automated tests have a few key characteristics:
- They’re repeatable – Automated tests provide test data and a pre-built environment. Then, after executing a function and measuring the results, it should clean up the data and environment to maintain a consistent state for future test runs.
- They’re determinant – Automated tests should be determinant, meaning the outcome is the same every test run. So, for example, an addition function will always return the sum of the two values even if the values themselves change.
- They’re not subjective – You cannot automatically test subjective matters, such as the intuitiveness of a new UI element. Generally, test automation requires a clear yes or no answer or a set comparison metric (e.g., a minimum loading time).
There are also several types of automated tests:
- Unit tests – Unit tests test a single function in isolation and don’t rely on databases or external APIs. Frequently, developers write them as part of test-driven development and must pass them before checking new code into source control.
- Integration tests – Integration or end-to-end tests test entire workflows across components. Since they’re more brittle and may take longer to execute, they typically only run before a new release or deployment rather than with each commit.
- Acceptance tests – Acceptance tests ensure that new code meets business requirements. For example, behavior-driven development workflows may produce executable scenarios that must pass before a sprint officially ends or new code hits production.
- Performance tests – Performance tests verify that the code meets efficiency standards. In particular, they typically prove if an application can withstand a specific load or measure how it holds up under pressure from multiple users.
Popular Test Automation Frameworks
Most software teams use frameworks to manage test automation. Rather than writing tests and running them from scratch, these frameworks provide rules and guidelines for writing test cases and tools to help run them efficiently. For example, they may offer object repositories, test-data handling methods, or ways to store and analyze test results.
There are several reasons to use a test automation framework:
- More efficient tests
- Lower maintenance costs
- Less manual intervention
- More test coverage
- Reusable code
- Easier integrations
Let’s take a look at five popular test automation frameworks.
#1 Selenium
Selenium is one of the oldest and most popular web test automation frameworks. With its rich history, the framework supports the most popular programming languages and has record-and-replay functionality to help those without programming experience. The framework’s WebDriver support also makes it a flexible option for any web application.
#2 Cypress
Cypress is one of the fastest-growing test automation frameworks for JavaScript applications. Like Selenium, the framework includes record-and-replay capabilities, making it accessible to everyone. But the framework also has unique and helpful features, like automatic waiting for asynchronous JavaScript functions.
#3 Appium
Appium is the go-to test automation framework for native and hybrid mobile applications. The cross-platform nature of the framework means that an organization can use virtually identical test suites for both iOS and Android versions of their mobile apps. Best of all, you don’t need to recompile the app for each test iteration.
#4 Robot Framework
Robot Framework supports Python and Java applications, making it a popular framework for developers specializing in those languages. Unlike many other frameworks, Robot Framework provides a well-defined structure for test suites and provides detailed logs and reporting to help troubleshoot and diagnose problems.
#5 Cucumber
Cucumber is a test automation framework for behavior-driven development. Unlike most unit or integration tests, Cucumber’s Gherkin tests consist of a human-readable domain-specific language that’s also executable as an automated test. That way, business and technical teams can ensure they’re on the same page when describing new features.
Scaling Test Automation with BitBar
Most integration tests rely on browsers, desktops, or mobile devices. While WebDriver enables headless testing, the most accurate and helpful tests require real browsers and devices. In fact, many organizations run the same tests against many devices to ensure no single machine breaks the application due to native constraints.
BitBar makes it easy to access a wide range of devices.
Historically, device labs have been the most popular way to run automated tests. But unfortunately, these labs came with intense cost and management overhead. Software organizations had to direct valuable engineering and DevOps resources toward updating devices and maintaining the optimal environment to run tests.
BitBar’s device cloud simplifies test automation by providing an easy-to-use API to access hundreds of browsers and mobile devices in the cloud. We provide integrations with Selenium, Appium, and Cypress, making it easier to expand your test coverage and scale up your tests without in-house capital expenditures.
The Bottom Line
Test automation has become an integral part of software development. Rather than running ad-hoc tests before deployment, software teams can build a comprehensive library of tests and run them with each new iteration to ensure nothing breaks. And with device clouds, it has become easier to scale these tests and improve test coverage.
If you’re interested in migrating to a device cloud, BitBar provides one of the most comprehensive device clouds with robust and easy-to-use APIs and integrations with popular test automation frameworks.