We are rapidly moving to a future of everything-automated, everything-agile, and everything-fast. Enterprises must cope with fast-paced digitalization while ensuring that quality is not sacrificed for software that also caters to user needs and drives business value. Companies will adopt exceptional solutions that are aligned with advanced software testing trends, which improve their existing practices. It’s almost become a necessity for micro, small, and medium-sized enterprises to leverage extensive automation techniques that yield software efficiency and robust product quality.
Can the economic downturn cause a negative impact?
As the economic downturn progresses, organizations often attempt to compromise their investments in test automation’s latest trends to reign in their costs. What results instead is a scenario where companies do not embrace updated approaches to application quality management and, as a result, do not accelerate and improve processes. This affects their revenue as product quality drops.
It’s important for organizations to understand the essence of investing in certain emerging trends in automated testing frameworks that deliver better products and cultivate positive user experiences. Carefully analyzing market trends can help identify methods that balance automation and software quality while offering cost efficiency at the same time.
Key trends in test automation
Here are a few of the key test automation trends to watch for in 2023. Organizations can leverage these approaches to offer optimal customer experiences while addressing constraints that affect daily operations.
1. Extensive adoption of low-code and no-code solutions
While these solutions are not new in the industry, 2023 is expected to see a rise in low-code and no-code automation. Low-code platforms provide abstracted, guided development, automated testing, and governance that can aid developers in rapidly building digital products. Gartner estimates that by 2025, 70 percent of new applications built by organizations will leverage low-code or no-code technologies. Compare that to 2020, where it was as low as 25 percent. This trend in automation testing has driven “citizen development” (essentially a non-technical coder) as well as affecting the function of business technologists. Both are personas outside of the IT organizations that can now create technology or analytics capabilities for business use.
2. A rise in collaborative robots
Collaborative robots or cohorts are directed to interact with humans in different shared professional environments. From lifting heavy equipment and products in warehouses, to intelligently moving and handling goods in the supply chain, robots can efficiently manage multiple tasks for small and medium-sized businesses. A greater inclination toward automation is predicted and will drive companies to invest more in physical and digital collaborative robots in 2023 to streamline complex workflows.
3. Shift-left testing
To deliver products on schedule with minimal defects while maintaining a budget is a priority for almost any organization. However, many of us face issues with balancing between budgets and time-to-market issues. With shift-left testing, testing teams can easily detect bugs and identify risks early in the product life cycle and thereby saving money, time, and effort invested. Development teams can collaborate to ensure detecting defects early on, ensuring that ideas are developed properly with low repair time and early release cycles. With the increased significance of shift-left testing, in 2023 organizations can expect enhanced efficiency, improved quality of product, and accelerated time to market.
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4. Revolutions in RPA using semantic automation
The focus on AI has only increased to improve business processes by streamlining automation and making things simple, agile, and interactive. Currently, we see developers provide specific instructions to robots to execute desired tasks. With semantic automation, using rule-based automation can be eliminated. Robots developed through semantic automation processes can execute the tasks by observing these tasks and emulating them.
5. Increasing Hyperautomation
Hyperautomation attempts to accelerate automation in as many processes as possible by adding a layer of sophistication that is not present in automation alone. Not only can a process be updated to work more rapidly, but it can also now leverage AI and ML to include skills such as analyzing, measuring, and reassessing input from a process. Hyperautomated processes can also offer benefits such as easy data sharing, real-time information access, improved productivity, and augmenting human intervention when needed.
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6. NLP technology and conversational AI
Intelligent automation (IA) employs a myriad of technologies with RPA at the center of its focus. Leaders in IA are pushing the limits of this technology by utilizing NLP and conversational AI tools to support customers, guide users through a workflow or streamline a process that has repetitive tasks.
7. Smart test execution
Smart testing is expected to see a rise in 2023 and use advanced test automation platforms that execute complex user flows. Smart test execution allows developers to test code through compliance channels that automatically identify which tests require execution for the particular check-in. This enables teams to run only what is needed (deltas) and not have to use long test cycles for every component of the build. The utilization of smart tests will not only help save time but also provides significant cost savings for business and IT resources. Additionally, if there are test failures, teams can quickly identify the correlation between the check-in and the smart tests to accelerate the progression through the product cycle.
Check out: Fundamentals of Test Harness
8. Multi-experience testing
Multi-experience testing is geared up to become a prevalent software testing trend. To meet the multiple demands of users across different verticals and industries, software development platform vendors are continually expanding their capabilities and value propositions to include diverse approaches to testing. Experiences like augmented reality, voice input and response, and complex flows that utilize different and non-traditional mobile devices at the same time, require platforms that are able to handle these scenarios effectively.
Also check: A complete guide to continuous testing
9. Autonomic system
The term autonomic system or autonomic computing is derived from the concepts of autonomic nervous systems that provide automatic response and action in biological processes. In the software development realm, this system is expected to work similar to the nervous system's autonomic behavior. In autonomic computing, the systems are expected to manage themselves by providing appropriate corrective actions that are completely automatic with minimal or no human intervention. Unlike traditional programming or simple autonomous systems, autonomic systems are capable of dynamically modifying their own algorithms with no external update, allowing them to swiftly adapt to new conditions.
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10. Composable applications
Unlike conventional applications that are self-contained and built as a single unit, composable applications leverage open and agile architecture that helps separate discrete app components. Components then can each be developed, scaled, and maintained per business needs. Independent software components are packaged as distinct business capabilities. Composable applications offer increased agility that enables enterprises to adapt their application infrastructure with changing business requirements. Additionally, these can help scale innovation and digital creativity, while making processes cost-efficient. As organizations aim to gain market momentum and customer loyalty, composable application technologies are predicted to have an increased presence.
11. Automated BioAuthentication
Biometric authentication has gained immense traction recently, by enabling users to login into their apps, validate actions, and certify identity using various methods. Enterprises are not only ensuring seamless app qualities but maintaining robust security as well in a climate that is showing increased threats to personal and business data. Biometric passwordless authentication is forecasted to grow exponentially this year. Technologies like Face ID for mobile phones make it easier for the user to access their device but, at the same time, provide a secure method that is tougher to overcome than traditional passwords. Software testing platforms must be able to handle this method of authentication as it becomes more common in today’s digital experiences.
How HeadSpin enables organizations to streamline test automation workflows
Platforms like HeadSpin aid enterprise efforts by future-proofing their test automation processes with multiple advanced AI and ML capabilities, which help them identify and analyze issues quickly. HeadSpin uses real bare metal devices to drive tests that capture critical performance KPIs. Organizations can collaborate effectively to isolate and improve performance outcomes for their digital experiences. Companies that use HeadSpin can leverage a secure cloud environment for end-to-end automated testing from over 90+ global locations.
2023 will witness several additions as per the latest trends in automation testing in order to keep pace with digitalization and consumer demands. Rapid advancements can often be overwhelming enough and cause more complexities in the software. Organizations in this situation will need to adopt architecture and frameworks that help converge business goals, consumer needs, and technological innovations effectively and offer optimized software quality and user experiences.
Q1. What is the basic goal of QA automation?
Ans: The primary aim of QA automation is to —
- Reduce or eliminate human intervention
- Accelerate development
- Improve reliability and efficiency
- Obtain quick feedback and shorten development cycles
Q2. What is browser automation?
Ans: Browser automation refers to testing software in a web browser by utilizing automated solutions for reducing the overall testing efforts and delivering faster and more accurate results efficiently. This helps build better quality software with less effort and enhanced user satisfaction.
Q3. What are the major benefits of test automation?
Ans: The key benefits of test automation include—
- Improved effectivity
- Rapid feedback systems
- Brand value improvement
- Widening test coverage