Test Automation: Latest Trends

Test Automation: Latest Trends

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5 min read

Quality is the best USP (unique selling property) that can create wonders by achieving huge sales numbers; no amount of aggressive marketing can push a bad product into the market, even if it does, the product can never sustain and create an ever-lasting impression. This may be the reason why software testing moved from being a mere support function to an independently operating sector. Gone are the days when testing would come into the picture only after the whole developmental process is complete, today with agile methodologies being implemented, testing has become an integral part of the software development lifecycle. It is introduced earlier in the process and performed simultaneously with development. In this way, the quality of the software remains top-notch.

Software testing has evolved over the past two decades. Initially performed as manual testing, it was time-consuming and reported inaccurate results due to its repetitive and mundane nature. Over time, the process evolved being powered by automation solutions to ease the tedious manual testing process, saving on time, cost, and effort. Today, test automation has become a significant software testing approach preferred by organizations worldwide.

Emerging Trends in Test Automation

The global test automation market is expected to grow to $28.8 billion by 2024. This massive industry has given rise to new trends every now and then to keep up with technological advancement and ever-changing customer preferences. Some of the popular trends in test automation are listed below.

Codeless test automation: Codeless test automation has been a revolutionary approach in the software testing industry. This is a fully automated process where the testers do not have to write codes; it helps organizations to considerably save on time and cost.

As the software testing process is advancing, continuous testing has been implemented to ensure reliable and stable results across the development pipeline. Under such critical scenario, code-based or manual testing can be futile. Codeless test automation can be performed effortlessly, and efficient results can be yield.

Cloud-based cross-device testing: Testing an app on all devices is quite a costly affair. Infrastructural setup cost was huge, and companies were not willing to invest a huge chunk of their budget only to set up devices for testing. This scenario gave rise to simulators and emulators, which are virtual devices mimicking the real ones. However, due to their inconsistent result behavior, organizations are moving towards Cloud-based testing otherwise known as Device Farms. Cloud-based frameworks are the popular choice for companies today, where they can run the tests easily on the Cloud and without having to make any huge investment. Companies can either opt for a public or open-source versions, or go for private Cloud; some of them even prefer hybrid models. No doubt, Cloud-based models are an innovative approach transforming the way testing is done today.

Risk compliance and security testing: Cyberthreats and breaches are rising at an alarming rate; only an efficient security testing can identify potential attacks and secure the system. Risk compliance and security testing are of paramount importance that cannot be neglected. It runs vulnerability scans across the system to identify any potential threat, and assesses the security of the IT infrastructure by utilizing weaknesses in a secured manner. Only a proper risk compliance strategy and efficient security testing can secure the system and create safe interface for users without the fear of confidentiality breach.

AI-powered testing: Automating testing was a revolutionary step towards improving the quality of the software. The introduction on AI (Artificial Intelligence) in testing has taken the software testing process to an exceptional level. AI-powered testing solutions have significantly reduced the human efforts while saving immensely on time. Performing repetitive tasks where highly tedious, which was eased by automation testing. However, AI-integration has redefined the process with its reasoning and problem-solving capabilities. AI-integrations have increased the productivity rate and agility tremendously, while improving resilience and reliability.

AI testing is gaining immense popularity for the ease and accuracy it offers. It's intelligent solutions to track defects and change operational strategy based on the customer behavior is by far the best way to perform software testing.

Shift-left testing: Shift-left approach focuses on testing and monitoring the app across the production environment. Here, the testing sequence is pre-defined, making it easier for the testers to write test cases as per the requirement. Testing is implemented in the early stages of software development; this practice helps identify and prevent defects early and deliver software of higher quality. Shift-left testing is popularly used by organizations to ensure better test coverage, save immensely on cost, and enhance customer experience.

Future of Software Testing

The use of codeless test automation has been on rise with organizations preferring to use it for the ease it offers without compromising on the quality. However, this is the current situation in the software testing trend, which will soon move to advanced testing solutions powered by Artificial Intelligence. AI-powered platforms have already made their presence in the market; they are predicted to soon be the most preferred software testing platforms. Its sophistication, efficiency, intelligent decision-making capabilities, self-healing nature, and faster test execution has made it stand out in the market. The craze for AI-solution is already increasing among companies and will be the future of software testing.

No matter what kind of technology comes up, whether codeless test automation or AI solution, the manual testing trend will always be a part of the process. Manual assistance is required for the initial setup of the process and monitoring the results at intervals to check if the process is working as expected. No technology has ever been created that can work independently without manual assistance.