Organizations are embracing remote and hybrid work models in the wake of COVID-19, putting in place the essential foundation to carry on. Technology has gotten closer to people's daily chores. Digital solutions will push and pull in the future.
Artificial intelligence breakthroughs that promise to ease touch points suffered by corporations and their consumers are being adopted by an increasing number of firms
As cloud solutions become more prevalent, Privacy by Design concepts is being reassessed as consumers grow more concerned and inquisitive about how their personal information is handled. The rapid use of new technologies, particularly the Internet of Things (IoT), blockchain, and artificial intelligence (AI) continues to drive drastic changes in software development. To cater to these needs, Intelligent Automation is the future of quality engineering. Only solid test automation infused with rapid implementation of new test techniques necessitates advanced up-skilling, tighter collaboration within and among teams, and a good grasp on the most recent technologies and approaches accessible to the quality engineering function.
While agile transformations have boosted the use of DevOps working techniques. Without a doubt, the most important criteria for every team are continuous integration and delivery. Utilizing the potential of this infrastructural requirement is the foundation of the future of high-quality engineering.
In this article, let us dive deeper into the top trends driving quality engineering.
Metastasizing of Tests
Designing test automation suites has always been the subject of debate and should be approached with more care. Teams must take into account a number of key considerations while formulating the strategy, such as the business domain, customer behavior, frequency of use, customer demographics, existing technical limitations, third-party integrations, etc. Only functional tests were traditionally the main focus when designing test automation suites. The requirement for the current solution offerings has expanded past the level of business validation, though. End consumers no longer just appreciate consistent functional behavior; instead, they are increasingly demanding improved user experiences, quicker processing, data security, etc.
The business validation checks should be supported by supplemental tests to achieve test spectrum saturation in order to meet this growing future need.
- Visual tests: UI designs are no longer just based on the “clean UI” approach; rather, they are now more carefully considered in light of the customer’s emotions and behavior as they use the application. To find the most appealing design for a feature, UI designers may use A/B tests as a tool. Regular visual checks should be instituted by test engineers together with feature functional validations with great care. The UIs are no longer a monolithic structure in terms of technical implementation. The innovative approaches to developing and creating frontends include component-driven development and micro frontends. Test engineers may need to incorporate component visual regression into their test automation framework to address these evolving technological needs.
- Synthetic Monitoring: A test engineering team is familiar with post-production smoke tests since they have been methodically integrated throughout various software development methods. It might not be a better deal for continuous production maintenance, given how much time and work goes into maintaining the standard functional test suits.
To keep an eye on the business applications’ health, there are many live monitoring solutions on the market. Most frequently, the production checks are handled on a regular cadence by the operations team. For routine inspections, test engineers can use these synthetic monitoring tools and integrate them with these external technologies.
- Left shift on API security tests: Data security is a requirement that must be met by all apps. Application testing was thought to include a separate vertical for security tests. Organizations are searching for alternative strategies to introduce security checks as early in the cycle as possible, as the number of unpleasant data compromise scenarios grows. There are many open-source tools on the market that can be used to check a solution’s security against the primary OWASP criteria. This aids in identifying the early development’s most glaring deficits. An effective test automation suite should allow for the start of such tests on the developer’s local machine.
Low code/No-code tools breaking down the barriers
Organizations are compelled to scale quality quickly due to the growing number of technological innovations. The current state of organizations makes it particularly difficult to find resources with exact skill matches or devote time to training and development. Low-code/No-code solutions like ACCELQ have been effective in knocking down the strong wall by assisting testing teams in developing test suits with quicker execution and clever self-healing mechanisms.
Because of their user-friendly UIs and reporting functionalities, low-code/no-code solutions also offer enhanced visibility during the execution of tests. Organizations are constantly looking for testing tools that can meet all of their needs and integrate nicely with their project management software and Devops practices due to the ever-shorter delivery timelines. The USP of ACCELQ is that it can smoothly integrate into any curve without requiring the development of any special solutions. A graphical blueprint of the application being tested is provided by ACCELQ's "Universe" (https://support.accelq.com/hc/en-us/articles/360026201612-Universe), which aids in rapidly finding the gaps inside the test scenarios. The test teams' confidence is boosted by the improved transparency and visual interaction.
API performance tests
One of the non-negotiable requirements in the solution package is application performance. Performance is the main factor that influences user experience, whether it be in a retail application or an enterprise solution. The average length of human attention has been dwindling over time; in one recent study, it fell from 8.25 seconds to 4.25 seconds. Organizations are faced with a unique problem in trying to strive for ongoing performance improvements.
I still distinctly recall that when the functional validation tests were completed, the application was handed to the central performance testing team for performance evaluation.. Functional testing teams were once more involved after the performance adjustments were made for a short regression to ensure there were no functional breakdowns.
In order to achieve faster delivery cycles, this serial execution can be taxing. The future direction in quality engineering calls for a left shift in performance tests, particularly on APIs. Introducing performance tests as a supplemental check in the existing functional test suit helps achieve the left shift of performance testing. ACCELQ provides this unique advantage of measuring web performance during test execution.
AI-driven self-healing test automation solutions
The principal reason for test failures in any test automation tool is often changing user interfaces. A decade ago, frontend development was homogeneous, the tech stack remained the same across solution offerings. Micro-frontends are popular at the moment. Micro-frontends are like microservices for UI layers; multiple teams working on a single UI with varying technologies is not a surprise. This implies that test suits with poor design are more likely to fail. We should be thankful for the new market solutions that incorporate AI to self-heal the testing with continuous modifications. Even though the majority of these tools are still in their infancy, ongoing advances are being made to improve the quality engineering process.
Utilizing AI/ML-powered tools will undoubtedly be a future trend in quality engineering. Test engineers need to get prepared and educate themselves on newer, more intelligent test design techniques. ACCELQ is one such No-Code solution which drives robust support in identifying the frontend changes and self heal continuously through machine learning.
Transformations through RPA and Hyper-automation
Hyper-automation, one of the main driving forces behind digital transformations, is designated as the future decade. The process of turning manual corporate processes into automated ones, or hyper-automation, minimizes the need for human intervention. Hyper-automation is a technique that combines a number of different technologies, including IOT, Big Data, AI/ML, RPA, and others. By integrating intelligent business process suites like iPaas solutions, organizations are attempting to enhance their overall business processes.
How does this impact my test automation suite?
Hyper-automation is a combination of technologies, as was already stated.Test engineering teams may focus more on conducting regression testing manually and fail to achieve a good ROI from their test automation suit. Businesses want to adapt to the new disruptive technology as rapidly as feasible; test engineering teams will be challenged to do so.
Test engineers must embrace intelligent test automation approaches to support business agility as quality engineering continually changes to meet changing business needs. Engineering teams should use more agile test automation frameworks to operate more efficiently and quickly. We cannot not allow the typical causes of test automation failures to impede our progress. It's critical to stay current with evolving digital trends and upgrade the automation suite to support the organization's entire operation.