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How AI is Making App Testing More Efficient

AI is taking many industries by storm, including mobile app testing. Learn how incorporating ai can lead to efficiency gains

In the realm of mobile app development, the quest for excellent user experience is unceasing. With millions of apps vying for attention in app stores, ensuring top-notch quality and efficiency is not just a goal; it’s a necessity. Enter the age of Artificial Intelligence (AI), where innovation meets necessity in a way that’s transforming the mobile app industry. AI is ushering in a new era by revolutionizing the testing process. This is done primarily through automatic test case generation and streamlined reporting. In this article, we dive into the ways AI is reshaping mobile app development, making it faster, more precise, and incredibly efficient. We’ll exploring how these cutting edge technologies are not just a game-changer but a cornerstone of success in the fiercely competitive world of mobile apps.

Artificial Intelligence: A Growing Business

Artificial intelligence has made headlines recently with it’s fast acceleration and integration with many industries. Since 2017, adoption of AI components has more than doubled denoting a huge corporate interest. An estimated 50-60% of organizations now use AI in some capacity with likely more on the horizon.

While overall organization adoption of AI continues to rise, integrating this new technology into mobile app testing has proved to be slow. Long, manual test cycles are often accepted as the status quo. But industry leaders are beginning to use AI-powered options for unprecedented efficiency gains. Let’s dive into two salient ways that AI can be integrated into mobile app testing.

The Future of testing: AI’s Role in Efficiency

Automatic Test Case Generation and AI

One application of AI is to apply it to generate test causes automatically. Automatic test case generation is the process of identifying and creating test cases for an application without the need for any human intervention. This can refer to both visual testing (app visuals) and functional testing (app behavior).

Our app testing platform is able to learn from different iterations and builds of the app. Accordingly, automatic test case generation allows for robust app testing without the need for user input. Furthermore, by learning from related apps, an automatic test case generation platform can suggest test cases that can be extended from other apps to improve and hold apps to a higher standard.

Sofy approaches this problem through ML and AI to generate context-based pathways in an application. By generating contexts, Sofy can learn certain flows and apply them to different applications of the same type. For example, the act of adding an item to a cart is similar among different retail apps.

Furthermore, Sofy can track app users and identify the most popular pathways. It then creates automatic test cases to verify that popular pathways are stable between releases. This is to validate that the user experience is not damaged by different builds in a constantly changing dynamic environment.

The improved efficiency from AI-powered automatic test case generation increases the availability of testers.  It also allows you to avoid what would otherwise be the necessity of hiring more test engineers. Applications can in turn offer better user experiences, better functional performance, and better visual design. AI-powered platforms such as Sofy will monitor the apps through intelligent test case creation.

To learn more about this process at Sofy, read our longer entry here.

Streamlined Reporting and Chatbot Help

Another efficient application of AI in the mobile app testing industry is by melding reporting tools with natural language processing. Co-Pilot, Sofy’s game-changing chatbot, harnesses the power of OpenAI to answer broad and specific reporting questions. With Co-Pilot, testers are able to ask questions in natural language and receive instant, accurate answers. Among other time-saving abilities, this AI feature is also able to generate a set of manual test steps that can be used to create a Manual Test. For example, testers can provide Sofybot with a link to their Confluence page and ask Sofybot to generate test steps based on the information provided. This feature allows developers to ensure that their test cases cover all the necessary features and functionalities of their application.

By harnessing AI to reach answers faster, testers are now able to focus on higher-level strategy instead of busy work. Furthermore, this offering speeds up the overall time spent on test cycles, adding back in time that would have been utilized less efficiently. With more available time, testing teams are able to more rapidly address bugs, and fine-tune more features. The end result is a stellar user experience.

Read more about Co-Pilot debut or features here.

The AI Advantage

In the dynamic landscape of mobile app development, AI stands as a powerful ally, streamlining reporting processes and providing automatic test case generation as an option. With its ability to bypass once human-centered busywork, AI is here to stay. This modern addition helps ensure mobile app testers spend their time working on more valuable processes. This increase in efficiency lends itself to faster bug fixes, shorter timelines, and an overall improvement in the user experience.