Call it DevOps or the Agile storm that has taken over the software product development space, the field of testing has seen a huge transformation in the last few years. As software testing has evolved from straightforward quality control to being an integral part of the customer experience strategy, it has resulted in heavily improved time-to-market for products. Enterprise testing teams have evolved to match up to the accelerated pace. Testing has become more central to product development, more integral to product strategy, and more key to product success. In many ways, there couldn’t have been a better time to be in software testing.
The year 2019 truly embraced Continuous Testing. Some estimates are that this strategy enabled organizations to achieve automation rates of as high as 85%. Organizations transitioned towards automation, ditching the conventional forms of manual testing more than ever. Usability testing and Behavior-Driven Development ensured that in 2019, the testing focused more on the end-user experience. Even technologies like AI and Machine Learning impacted the testing scenario heavily, although the impact was slow.
As 2020 dawns, let’s see how the test automation trends from 2019 are changing in 2020. In this article, we’ll discuss the top trends in test automation that will set the tone for the year 2020.
1. Hyper Automation
Hyper automation means bringing together multiple technologies to carry out test automation at a faster pace. Hyper automation quite literally means ‘hyper’ or ‘active’ automation testing, which is carried out with minimum human efforts, effectively saving time as well as money. According to a study by Gartner, Hyper Automation is one of the top strategic technologies to look forward to in the year 2020. Hyper automation makes use of a portfolio of technologies including Machine Learning (ML), Artificial intelligence (AI), IoT, Neural Networks (NN), Robotic Process Automation (RPA), and Deep Learning (DL). Hyper Automation could bring forth one of the most sophisticated means of testing.
2. DevOps continues to dominate (DevTestOps)
Dominating the product development space for 10 years now, DevOps is one trend that won’t lose its thunder. DevOps is on the rise -always. Since it is an amped-up extension of Agile methodology, is easy to buy into. For products, the focus is more on continuous development along with continuous testing. Since every action in the DevOps cycle is automated, the testing has to be aligned with the cycle, test cases are 100% automated (well that’s the aim, anyway) and the entire software development effort is highly coordinated. To ensure no loose ends in this cycle DevTestOps has come about. DevTestOps integrates testing deeper into the DevOps process. This ensures that product changes are quick and do not impact the quality. With DevTestOps, the meantime to identify and fix issues will reduce, improving the overall testing process, effectiveness as well as speed.
3. AI and ML-based tools
Intelligent automation, as it is popularly called, could be one of the biggest trends to dominate the test automation market in the year 2020. Artificial Intelligence and Machine Learning-based tools could replace human efforts involved in defining test automation strategies, building automation frameworks, and validating the tests. We have also written about how to accelerate software testing with the power of AI and ML. While the technologies have been talked of for a while, 2020 will see a significant rise in the use of AI and ML in testing. More and more QA teams could make use of Artificial Intelligence and Machine Learning in various elements of test automation including predictive analytics, log analytics, and defect analytics.
This could give rise to autonomous testing, where AI and ML will provision automated test creation and execution, without any manual code creation required. Although it’s early days yet for AI/ML-based testing, it will be imperative for the QA and Agile teams to acquire new skill sets to effectively align to new updates in test automation.
4. IoT Testing
The Internet of Things has dramatically changed lives and business processes and we’re not complaining. The rise of enabling technologies like 5G will make IoT central to a variety of enterprise business processes. As more IoT devices start playing a role in enterprise business processes, IoT testing will come more into focus. According to a prediction by Gartner, the number of IoT devices will reach up to 20 billion in the year 2020. With these many IoT devices around, it is imperative to extensively test these devices for security, compatibility, scalability and data integrity. 2020 will see a huge rise in the performance testing of apps for IoT and IoT devices too.
This will also lead to an increased demand for multi-experience testing, which means that any applications have to be tested to run and perform on multiple device types including wearables, AR and VR devices. IoT devices will open the data floodgates. Enterprise product testing will have to factor in that volume, velocity, and variety of data and how the solution fares in that situation.
As the technology world laps up new methodologies, it becomes necessary for enterprise software new products to keep up. That is a software testing problem of massive magnitude. With these testing automation trends set to dominate the year 2020, it will be interesting to see how enterprise product QA teams up their game to stay ahead of their curve.
FAQ
What are the current trends in test automation for enterprise products?
Current trends in test automation for enterprise products include the adoption of AI and machine learning to enhance test coverage and efficiency, the integration of continuous testing within DevOps pipelines, the use of test automation frameworks and tools that support cloud-based environments, and the emphasis on shift-left testing to identify and fix issues earlier in the development cycle. Additionally, there is a growing focus on testing for security vulnerabilities and ensuring compatibility across diverse platforms and devices.
How is AI impacting test automation for enterprise products?
AI is revolutionizing test automation by enabling more intelligent and adaptive testing processes. AI-driven tools can analyze vast amounts of data to identify patterns and predict potential issues, automate test case generation, and optimize test execution. This helps in improving test accuracy, reducing manual effort, and accelerating the overall testing process. AI also assists in detecting anomalies and providing insights into test results, leading to more effective bug identification and resolution.
What role does continuous testing play in the test automation landscape?
Continuous testing is a crucial component of modern test automation, especially in environments that embrace Agile and DevOps methodologies. By integrating continuous testing into the development pipeline, teams can ensure that testing is performed consistently throughout the development cycle, rather than only at the end. This approach allows for early detection of defects, faster feedback, and quicker delivery of high-quality products. Continuous testing helps in maintaining the health of the software by providing immediate insights into the impact of code changes and ensuring that new features do not introduce regressions.
How do cloud-based environments influence test automation strategies?
Cloud-based environments significantly influence test automation strategies by offering scalable and flexible infrastructure for running automated tests. They enable testing across various configurations and platforms without the need for extensive on-premises hardware. Cloud-based testing tools provide access to a wide range of environments, allowing for comprehensive testing of applications under different conditions. This flexibility supports the testing of applications that need to perform well in diverse and dynamic cloud environments, leading to more robust and reliable products.
Why is shift-left testing gaining popularity, and what are its benefits?
Shift-left testing is gaining popularity as it emphasizes the importance of testing early in the software development lifecycle. By moving testing activities to the earlier stages of development, teams can identify and address issues before they become more complex and costly to fix. This approach promotes collaboration between developers and testers, improves the overall quality of the product, and reduces time to market. The benefits of shift-left testing include faster feedback on code quality, early detection of defects, and a more efficient development process that leads to higher customer satisfaction.
