Building a Five-Star App: Utilizing AI and Automation to Enhance Mobile Testing
Software development teams need powerful, low-cost tools to deliver high-quality mobile app experiences. AI and automation offer a solution.
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In today’s technology-driven world, it’s all about the smartphone. 85% of the global population owns a smartphone — an estimated 6.8 billion people — and 73% of total e-commerce revenue is generated from mobile devices.
Due to the reliance on mobile devices, the need for quality apps has gone up. Users expect flawless, frictionless experiences each time they interact with their devices, and this puts immense pressure on organizations to deliver high-quality, high-performing, and highly secure apps. Even further, users will abandon apps with poor performance; 81.9% of users will abandon an app within two weeks of downloading it, and half of mobile users (50%) won’t even consider using an app with a three-star rating.
With this increased demand, software development teams need the right tools that not only allow them to deliver high-quality mobile app experiences but are also easy to use, low-cost, and powerful. The solution can be found in AI and automation.
The Power of AI and Automation in Mobile Testing
To create a mobile app that meets end-user demands and standards, developers need a solid testing process that ensures the app put on the market is the best it can possibly be. A strong mobile testing process fully integrated into development workflows can guarantee consistent quality across all mobile apps and create exceptional customer experiences.
However, developing a solid testing process has been a challenge for some organizations as it can require a lot of time, money, specialized knowledge, and manpower. Fortunately, AI and automation can help alleviate these issues and empower developers to create better testing processes and better apps.
There are three ways, in particular, that AI and automation can help enhance mobile testing:
1. Build Test Cases
Before you even begin writing or running tests, it’s important to understand the target users and define the coverage of the application, common user workflows, and unexpected workflows. This is done by creating test cases. AI is a useful tool to create large sets of test cases and vastly accelerate the coverage and number of tests.
For example, AI can assist in generating test cases for mobile applications by analyzing the application's code, user interface, and product requirements. AI has the ability to identify potential areas of vulnerability or risk and automatically generate test cases to evaluate these areas.
Further, easy-to-use, AI-based test management solutions can be fully integrated into issue-tracking systems and allow any team member — regardless of experience or skill level — to contribute to creating test cases.
2. Run Tests
After building the test cases, software developers must run multiple different versions to ensure that the app they’re putting on the market is the best it can be. AI and automation can also help create the actual mobile tests, ensuring better test coverage and reliability. AI-based test automation tools can ensure the stability of tests and detect when the test has a false positive or error.
Additionally, for a continuous development process, you need a testing solution fully integrated into your CI/CD pipeline. Automation can trigger test runs, check the functionality of new code, and accelerate the testing of a large set of use cases to quickly enable the build process. This allows developers to fully integrate mobile in their CI/CD workflows, supporting faster delivery of changes and features.
Utilizing AI and automation to build mobile tests helps take the grunt work out for developers while also enabling more employees to partake in the process. Overall, these tools can help expedite the testing process while also ensuring the overall quality of the app.
3. Pinpoint Failures
Lastly, AI and automation can help in the critical detection and analysis of errors and issues within mobile apps. For instance, AI-enabled analytics provide the ability to holistically see and understand mobile interfaces. Automation, on the other hand, executes the tests at scale and speed, creating test results and allowing AI to identify patterns that may also indicate potential bugs and defects. This allows developers to detect failures better, allowing for the optimization of native features, performance, and platform-specific UX to create the best app possible.
With AI and automation, developers are equipped with the right tools to catch critical performance issues in real-time, track key performance indicators related to network, location, CPU, and more, and deliver superior mobile experiences to customers.
Building a Five-Star Future
In a smartphone-dominated world, the demand for seamless mobile experiences is at an all-time high. To meet this demand, mobile testing plays a critical, if not paramount, role.
AI and automation provide a lifeline to app developers by streamlining the mobile testing process and ensuring that test cases are built and run efficiently and accurately while also catching issues and bugs before the app has a chance to hit the market. Mobile testing is key to a five-star app, but without AI and automation, developers may find themselves scrambling for users.
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