Autonomous Testing: The Next Wave of Test Automation

The software testing market is estimated to surpass USD 70 billion by 2030.
-Global Market Insights

The past few years have seen significant digital transformation initiatives. Businesses have become digital-first, with more software being built and customized. Technology organizations are focusing more on the continuous evolution of their agile software development, attempting to achieve the highest level of automation. As a result, essential aspects such as bugs, glitches, and user experience are often overlooked. In a race against time, the developers often misinterpret specifications, write weak codes, overlook security aspects, and test software insufficiently. This leads to software inefficiencies, damaged reputations, and financial losses.

Various instances of high-profile software failures in the recent times have illustrated the need for organizations to strengthen their software development lifecycle and automate failure analysis by implementing new software testing strategies. As organizations and customer demands are evolving rapidly, testing practices also need new approaches. Autonomous software testing has emerged as a great approach to reduce manual intervention, accelerate delivery cycles, and rapidly scale operations to meet the demands of today’s fast-paced market.

Strengthen Test Automation with Autonomous Testing

Autonomous testing is a new test automation approach wherein software tests can be created and maintained, and executed autonomously, and the resulting outputs can be analyzed without any manual intervention. Autonomous testing will be a major trend in 2023 and it will enable QA professionals to save significant time spent in writing long codes of complex codes and maintaining test cases. Below are some benefits that organizations can expect from their investment in autonomous testing:

1: AI and ML To Reinforce Software Testing

The autonomous testing leverages new-age technologies like Artificial Intelligence (AI) and Machine Learning (ML). AI and ML technologies are empowering the QA professionals to strengthen test management and optimization. Leveraging an AI-based capabilities in a test automation software, teams can execute multiple test cases at once and test their application rapidly. AI-based testing systems empower QA teams to manage their test projects by automating test reporting, test scheduling, and test case prioritization. Thus, it enables testing teams to deliver applications faster, reducing the time-to-market.

Additionally, ML capabilities in a test automation solution deliver self-learning capabilities to machines. It can learn from past executions, historical data, and intelligent algorithms fed into the systems, and optimize the test cases based on learnings. Thereby, expediating the testing process.

2: IoT Performance and Load Testing to Validate the Quality of IoT Apps

In the age of interconnectivity and the Internet of Things (IoT), new data networks are created every day, which enables people to communicate with physical objects — “things” — that are embedded with sensors, software, and other technologies enabling the “things” to communicate with each other. This technology trend has led to the evolution of concepts like “smart” houses, “smart” cities, etc.

However, to ensure the success of these revolutionary ideas, it becomes crucial that the networks through which the data is transferred, the services, and the security devices are tested through performance testing. Organizations working with IoT require an autonomous testing ecosystem sufficient to measure and improve the performance of networks and security devices. Only then can they guarantee success, security, and maximum adoption of IoT.

3: Utilization of Chatbots in Autonomous Software Testing

Historically speaking, integrating enterprise applications with test management platforms posed various challenges. However, due to advances in Natural Language Processing (NLP) and autonomous testing, users can seamlessly integrate software testing with Chatbots and automate the entire test management process, from the development of test cases to execution and autonomous test result reporting. During the test phase, users can use Chatbots to add test cases, run them without manual intervention, assign tests to testers, and get a consolidated test report generated at the end. Additionally, these test management Chatbots empower business users to keep track of testing and stay on top of their development projects.

2023 will see organizations focus more on Autonomous Testing

Quality software that can transform processes, reduce efforts, save costs, and deliver outstanding user/customer experiences have been the flagbearers of digital transformation. However, the incidents with software quality in the last few years have duly illustrated the need to test any release more in-depth before release. Autonomous testing will evolve significantly in the upcoming year to support the challenges organizations face. To stay relevant in the competitive market, organizations must understand the latest testing trends and incorporate testing technologies to streamline their process and mitigate errors.

At AgreeYa, we enable organizations to test and ensure the best quality software rapidly. Our testing and test automation services and solutions help businesses move ahead in their digital transformation journey with intensity.

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