The mobile application development industry has reached new heights every year in the last decade. Practices such as Mobile DevOps have strengthened the global mobile app development infrastructure, enabling creators to speed up their app development processes drastically. But, if there’s one area where the mobile application development industry is still lacking, it’s mobile app testing.
Despite the prevalence of various automated testing tools, keeping up with the fast pace of mobile app development has always been a significant challenge for mobile app testing experts. Can Artificial Intelligence (AI) or Machine Learning (ML) tools speed up this aspect of mobile application development? Well, companies in China have already published over 41,000 research papers on AI, many of them focused on mobile app testing. How is the Western World responding to these advances? Let’s explore.
The Key Challenge in Mobile App Testing
For all mobile app developers across the world, one aspect of mobile app testing is the most excruciating: Human Interface Guidelines or HIG. These guidelines outline how apps look like to end users on mobile. A well-tested HIG will consistently deliver amazing user experiences. But, understanding the user experience in standard mobile app testing processes is very difficult. That’s why the world’s top app testing companies are applying AI to assess the results of HIG performance tests.
Any time test cases are run on devices connected to these AI-powered platforms, smart issue detection engines run various assessments to classify, measure, and rank issues observed during the tests. These assessments provide highly detailed insights into end-user experiences. Be it slow loading times, poor graphical qualities, server misconfigurations, or networking errors – all aspects of the user-side app and device performances can be quickly assessed using these tools.
Access to these insights and detailed metrics enable app developers to correlate major problems with the app (for instance, the homepage taking too much time to load) with the root causes behind the problem. For instance, homepages usually take too much time to load because of certain HTTP error codes. Unlike traditional app testing tools (or manual app testing processes), these AI-powered app testing tools are functional 24×7. They constantly deliver new insights into important issues that negatively impact the quality of user experiences on the app and on the users’ devices.
A recent study reported that 64% of all leading companies in the U.S. have already adopted AI tools to better their customer experience management (CXM) processes. AI tools being used to deliver better user experiences in mobile apps isn’t a surprising phenomenon. App developers want to cut down testing costs, and these AI-powered testing tools offer the perfect cost and time-effective solutions.
Other Major Advantages of Applying AI for Mobile Testing
When AI tools were first introduced in software testing, the primary goal was to minimize testing costs, time, and the use of complex codes. The shift towards code-free testing has been slow but promising. Developers no longer have to spend hours creating scripts for tests. Here’s why AI tools and mobile app testing makes the perfect combination –
Supports Manual Testing Processes
Software testing experts have to deal with various limitations while manually testing the codes of various mobile apps. AI tools enable them to conduct “precision testing” of apps. These tools optimize the testing processes using smart test modules. Unlike manual testing tools, AI-powered tools can easily run multiple simulations within seconds and quickly learn how to mimic human behavior using the data from assimilation machines. Overall, the insights these tools provide greatly ramp up the speed of manual testing processes.
Creating an Era of Codeless Testing
When mobile app testing experts plan their test procedures, they have to determine which tests are suitable for the specific mobile software they’re working with. Different mobile apps require different types of tests. There’s no need to execute the same types of tests for all apps. To understand which test cases will impact app performances the most, app developers need to create code monitoring systems. These systems ensure that all mobile testing procedures are being carried out using well-defined scripts. This excruciatingly long process can only be carried out by testers with special skills. Since small-scale developers can’t afford to employ such highly skilled workforces, they prefer AI-based testing, which depends on codeless monitoring processes. Overall AI-based mobile app testing procedures are executed faster and provide much better results than testing procedures that involve complex code monitoring systems.
Makes the Work of Quality Assurance Engineers Easier
Quality Assurance engineers receive a lot of assurance from AI-enabled testing procedures. The need to run countless scripts to get one positive result is completely eliminated. They can focus on brainstorming different tests and applying them to improve other aspects of their mobile apps.
AI-enabled mobile app testing processes are constantly improving. The large number of innovations that AI-based testing tools have introduced to the field of software testing over such a short period is nothing short of splendid.
