With the spurt of digital business that is fast blurring the line between physical and the digital worlds, mobile apps have become indispensable. In this age where there is an app for almost everything, user review is one of the primary criteria that decides the fate of an app. Therefore, it has become more critical than ever to offer a great customer experience on mobile apps. Overlooking QA and app testing best practices can ruin the chances of a great user experience ultimately leading to the short shelf life of an application.
According to statistics, mobile app downloads will reach 258 billion by 2021, a 45% increase from 2017. By 2022, the mobile app industry is expected to generate nearly $156 billion due to a steep rise in mobile app usage.
Mobile app testing is the process of testing a mobile application for its usability, functionality, performance, and security according to the user’s requirements. It guarantees excellent quality before the app hits the marketplace.
Mobile app testing is a vast landscape that requires testing for the various functionalities, OS versions, and mobile devices. The increase in demand for mobile apps in the digital market within a short turnaround time has spurred the role of artificial intelligence (AI) in tackling the gaps in mobile testing. AI automation testing helps in faster test releases, reducing the cost, effort, and time compared to manual testing.
AI automation tests also make implementation, execution, and analysis of the test results effortless. The codeless automation approach saves testers from the cumbersome processes of test script creation and provides accurate results.
With its wide range of capabilities, AI finds its application in mobile testing to augment test processes and improve overall test performance. Check out some of the AI applications in mobile app testing as mentioned below:
Mobile application testers face several challenges, such as unreliable testing environments, continuous testing due to agile development, distributed testing teams across the globe to name a few.
AI-based cloud infrastructure addresses these problems by providing an optimal test environment and automation services based on the requirement. AI cloud brings the best of both worlds by combining the potential of artificial intelligence with the existing capabilities of the cloud. AI cloud mobile testing enables one to test the mobile apps in simulated devices or real-time remote smartphones.
A cloud test infrastructure allows 24 x 7 access to the test resources, running several test cases in parallel without restrictions, scalability, cost savings, and high efficiency. The AI feature in cloud testing provides valuable insights from the test results data, thus improving the mobile app.
Mobile app debugging is the process of identifying and removing the bugs and errors in mobile apps. AI assists in debugging by monitoring the target mobile apps for glitches, system crashes, interface malfunctions, or any error preventing the app’s smooth functioning.
AI-based debugging can automatically detect the errors in the code, unlike the manual process that could take even weeks to detect a single bug. AI automation saves a considerable amount of time and effort spent manually detecting the errors for debugging the application.
As much as it is essential to test the mobile apps in various mobile device models, it is equally important to test them in different versions of OS. The mobile app cannot be tested solely for the latest version of the OS but also for the other supporting versions to make it accessible to a broader audience.
AI testing automation for mobile apps helps in running unlimited tests on real devices with different OS versions. It helps to identify which OS versions best suit the app and to present the compatibility report.
AI testing enables running hundreds of test cases in parallel for numerous connected devices within a short period. Once the AI test is programmed, testers can reuse it for several similar cases bringing down the cost. Monitoring the test script 24 x 7 is a tedious process involving too many team members to overview it. But AI automation saves the manual effort involved and simplifies the entire process.
Continuous testing and continuous feedback in a DevOps environment help detect the bugs early with the help of AI-based monitoring tools. The AI monitoring tools’ Machine Learning (ML) capabilities identify and understand the scenario and provide customized suggestions for better results.
AI provides codeless automated testing without the need to write code to run the test scripts. This codeless automation powered by AI reduces the requirement for programming knowledge, is platform-independent, and reduces test maintenance.
Mobile app testing has become more challenging with evolving mobile devices, varying OS versions, and other configurations. In today’s digital world, the quality and performance of a mobile app are directly proportional to the customer experience, which could define its success or failure. Hence, businesses must leverage the power of AI to address the gaps and issues in mobile testing and consider investing in it for a great customer experience.
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