Mobile app testing is one of the most crucial phases that occur in the process of launching a new mobile app into the market, without this critical stage taking place, it is impossible to gauge the success of your mobile application. Think of it as a vehicle endurance test in terms of automobiles.
Some of the main aspects that are tested during this process are the screen resolution, GPS functions & screen orientation. The app’s functionality, usability and consistency is checked on a variety of OS to give the tester a holistic understanding of current market. These can be an automated or a manual process. Mobile app testing can be effectively done in three ways;
By checking the functionality of the app by analyzing business flows, testing the user interfaces and checking its credibility across multiple platforms. A real-world scenario approach can also be taken to handle challenges one will face such as network issues, background application disturbance, and user errors like gestures, real devices are preferred in this case over simulators. A non-functional testing also exists, where other aspects of the app such as security, accessibility, performance, availability and API is tested.
The main issues that occur in mobile testing are; Repetitive tests that occur due to slow test speeds, need for experienced testers to operate the testing device, inaccessibility of mobile devices that are currently in the market.
BOTm recognizes the gap that is present in the mobile testing domain and addresses them effectively with a highly efficient tool that significantly reduces testing speeds (Up to 5x) and creating a user interface that is simple and easy to understand, making it suitable for testers who might not have an in-depth understanding of coding. We provide access to the current mobile devices that are running in the market, which helps in achieving a well-rounded testing experience to verify the functionality of the app across different platforms as well as individual handsets. The tool is armed with the power of artificial intelligence and machine learning which ensures that the testing process is recorded and stored for similar use in future scenarios.