Software Testing Is Geared Up For The AI Revolution

Software Testing Is Geared Up For The AI Revolution

Artificial Intelligence (AI) is making its presence everywhere – from performing complex medical procedures to providing a delightful customer experience. By complementing and augmenting human capabilities, Artificial Intelligence solutions are disrupting various functions across industries. The software development and testing industry are no different, with more companies deploying AI-powered tools for various tasks. 

Bridging The Gap 

Given the hyper-competitiveness and economic volatility, agility has become the buzzword for businesses to sustain and thrive in the market. Subsequently, the size and complexity of software development are escalating, but the delivery periods continue to shrink. Also, daily updates on applications are frequent now. It has become an ongoing need for testers to increase their efficiency in software testing, and that is where AI-powered tools come in. 

With the help of Artificial Intelligence solution providers, enterprises can streamline their software testing processes and make software development lifecycle more proficient. It is now widely deployed to check the quality of the applications on various parameters like performance, stability, cybersecurity, etc. and identify its various use cases. 

Advantages of AI in Software Testing 

More than 80% of the software testing process is mere repetitive tasks and deploying AI tools for the purpose can significantly save time, capital and resources for businesses. It contributes largely to building smarter, productive and efficient applications for the end-user. 

The other significant benefits of using AI-powered tools in software testing include: 

  • Better and unfailing accuracy – Humans can err, but not AI-powered tools. While errors are inevitable during manual testing processes, automated testing can perform repetitive tasks with full efficiency. Thus, testers can automate repetitive activities and focus on tasks that only humans can perform. 
  • Improved productivity – By taking advantage of Artificial Intelligence service, testers can ensure precise and continuous software testing at a rapid pace. Furthermore, it can go beyond the limitations of manual testing by simulating thousands of virtual users in an application.      
  • Enhanced flexibility – Traditional testing scenarios are limited to singular selector or paths, but automated tools increase the overall scope and depths of tests. It can follow a more flexible testing process; hence better product quality is expected. Moreover, it is equipped to learn relationships between different segments of documentation which is otherwise hardly possible. 
  • Allows visual validation – Automated testing tools allow visual validation and pattern recognition which is yet another major advantage for development and testing teams. It can discover visual bugs by enabling visual tests of apps. With Artificial Intelligence development, the capability of tools extends to distinguishing dynamic UI controls and evaluating them in pixels.
  • Defect detection – When test data grows, more bugs will be recognized. In manual testing, it is difficult to write and execute hundreds of test cases, and bugs may remain unnoticed for long. In the automated testing process, codes are autocorrected, and bug tracking becomes more effortless. 
  • Faster time-to-market – With the wise use of AI-powered testing tools, the time for product development can be dramatically changed from months to hours. It is a significant advantage for businesses wanting to make software product releases and updates more frequently. 

The Bottom-Line 

Given the increasing technical complexities and shorter delivery cycles, AI-powered tools become the saviour for software testing teams to keep up with the pace. The primary aim of involving AI in testing is to decrease development lifecycle, and improve the efficiency of the product. 

Although automated tools are widely used for reducing mundane, and tedious tasks in development and testing, AI in software testing is still in its infancy. With AI making deeper inroads into software testing, we can expect the release of higher quality applications at a fastened pace.