Mobile applications are no less than the genie of Alladin’s lamp of the 21st century. Mobile applications of today’s time have the full potential to meet the neverending demands of their user base. This dynamic nature of the mobile app industry has led to the huge popularity of mobile applications.
So the need of the hour is to develop technologies which are faster as well as qualitative. For developing high-performance mobile applications, organizations are forced to use high tech and futuristic solutions like Artificial Intelligence. In this blog we will have an overview on how AI can boost the intent of achieving quality@speed for mobile app development.
AI enhances DevOps
DevOps is famous for boosting the speed of software development as it provides ready to be deployable code. In devOps software development as well as testing takes place in every stage of the development cycle, hence it receives feedback in earlier stages with the help of monitoring tools.
These monitoring tools with the help of machine learning algorithms can be trained well enough to analyse and provide feedback to the next stages of the development and speed up the complete process. In this way AI can increase the speed of the devOps in multiple folds.
AI can be used for Object Identification to avoid flaky test cases
AI can be used for Object Identification which was traditionally performed with the help of Identifiers and Xpath locators. To perform this we will use the machine learning algorithms which will be trained to identify the objects once the package of AI is instantiated. In this way we can attempt automating the test cases with the help of AI based packages and drivers which helps in identifying the objects effortlessly with the help of trained machine learning algorithms.
AI increases the speed of Automation
Mobile application testing has dynamic requirements. For example if any last minute issue arises then you need to dig the complicated and lengthy test suites like functional and regression test cases which is very time consuming. Also we receive a lot of data from continuous testing test suites. But machine learning languages can be used to locate the common patterns. This will help in knowing what is the least number of test cases required to make a small change in the test suite.
AI can strengthen Manual Testing
However popular the automation testing becomes, manual testing cannot be neglected.Non functional and UI testing requires manual testers and their efforts can be minimised by implementing self exploring apps to measure if all the existing functionalities and user flow works as expected. QA teams can use these AI testing bot to enhance their testing efforts and specially the non functional test cases. Also they would get the best coverage in minimal time.
AI Testing Bot
Implementation of the AI Test Bot was another feather added in the world of mobile app automation testing. So most of the AI Testing tools emerging in the market leverage AI Testing bot to help them with software testing. It can also be used for testing mobile apps. pCloudy provides an AI based testing bot called “Ceritfaya” which provides a health checkup of the mobile app under test. It scans the complete app to test if it functions as expected and also provides suggestions to improve the performance of the app.
The quality of a mobile app is of utmost importance for it to perform well in the market. So advanced technologies like AI can help in making the testing process efficient by increasing the speed as well as quality of testing.
AI uses deep learning and predictive analytics to provide automation. Similarly AI can be used in automating various processes used for testing and development of mobile apps. All we need to do is creatively implement AI to utilize its full potential in app development. In a dynamic industry like mobile application, AI proves to be a boon which would improve the Agile cycle both in terms of speed and accuracy.