“Never let the same bugs bite you twice; or rather, never get bitten”
What is Automated Software Testing
Ever wondered how engineers at Meta, Amazon, Twitter, Instagram, and your favorite social media platforms churn cool new features and updates in little or no time difference from the last feature or update, all without glitches, bugs, and no visible disturbance on your end? Yes, I know you’re suddenly curious. Automated software testing plays a major role in all that process. But, why automated software testing?
We presently are in a digital age where progression is inevitable and for businesses to survive, innovation and adaptability are vital. The way we live, work, and play has evolved and so is the way software testing is done. Software testing like our digital age has progressed and metamorphosed, unveiling a more cost-friendly, more effective, and time-saving approach called Automated Software Testing.
Automated software testing is the application of software tools to automate the human-driven manual process of reviewing and validating a software product. In this digital age, we prefer not to talk about the function of test engineers but about test engineering as a set of skills and activities that can be performed by people with different roles. The skills needed to set up digital test engineering are numerous. It is not feasible that all skills are gathered in one person, the benefits of automated testing are more cost-friendly, time-friendly, and effective ways to set up your testing process to suit your needs.
Over the years, the software industry has been creative with ways of delivering codes faster and most importantly safer with better quality using methodologies like continuous integration development, agile development, and DevOps.
Automated software testing makes these mentioned methodologies seamless, thereby eliminating the need for hotfixes, enhancing user experience, and above all being more efficient and effective in testing software solutions. Automated software testing majorly makes use of automated software testing tools that can playback pre-recorded and predefined actions and also compare the results to the expected behavior and then notify the success or failure of the test.
I align with the thoughts that automated software testing is the best way to increase the efficiency, effectiveness, and coverage of your software testing while still saving valuable time and cost. Now I’m sure you are thinking, how does automated testing work?
How Automated Testing Works
Organizations could either implement test automation frameworks or very less often build their automation test tools. The test automation frameworks implemented by organizations include common practices, testing tools, and standards, with data-driven and keyword-driven test automation frameworks which are very common as are frameworks for linear scripting and modular testing.
The linear scripting test framework suits small applications because it enables the use of a test script with little planning, but does not support reusable scripts. In modular testing frameworks, a software tester creates scripts as small, independent tests to reduce redundancy.
Data-driven frameworks enable software testers to create scripts that work for multiple data sets and provide wide-quality coverage with fewer tests than modular options. Keyword-driven testing frameworks use table formats to define keywords for each function and execution method; software testers without extensive programming knowledge can work with the keywords to create test scripts. The hybrid-driven framework is by far the most suitable as it combines two or more practices to have the benefit of both practices.
Open-source test automation tools and frameworks include Selenium, Robotium, and Cypress. Robotium helps testers write automatic user acceptance, functions, and systems tests for android devices. Selenium on the other hand can automate and run test parameters across multiple web browsers and in various programming languages such as Java, C#, and Python. Cypress covers end-to-end integration and unit tests all within a browser; it also allows access to distributed object models in the browser and provides a debugger for further tests.
Automated testing can be used or applied in any test case or scenario but it is best applied to tests that are too laborious and time-consuming when performed manually, tests with multiple data sets, tests that are performed on different hardware or software configurations or platforms, tests on frequently utilized functionality that introduce conditions which elevate risk and even test that frequently generate the human error.
Future of Automated Software Testing
Imagining the future and the measure of the impact that the future of automated software testing brings, it is an open secret that the future of automated software testing is Machine Learning and Artificial Intelligence.
Presently, to develop a UI test you must either write a lot of code or have a tester manually click through UI, which can be very uncomfortable and time-consuming. In the nearest future, test-generation tools will employ AI to design and perform UI tests on a variety of platforms and also mimic human behavior by tapping buttons, typing text, and swiping images while filing Jira tickets or issuing tickets for developers when problems are discovered.
Taking another look at how Machine Learning plays a vital role in the future of automated software testing, it is crucial to talk about an innovative method called predictive test selection that is gaining interest for enterprises battling with high test suite runtimes. For example, Google and Facebook have built machine-learning algorithms that analyze incoming changes and only execute the tests that are most likely to fail.
With the prolific advancement of technology and the digital age, firms and companies all over the world will continually need to invest heavily in automated software testing if they are to remain relevant and constantly evolve and meet their end users’ needs. Automated software testing also provides software development teams with information about data tables, memory contents, and other statistics necessary for the application’s performance.