Making QA smarter with AI
Till now Artificial Intelligence (AI) was heard as a technology capable to transform the future to the extent that every connected device would be smart and auto-responsive. The technology is smart with the inclusion of sensors, data recorders and smart analyzers with real-time data reporting. In simple terms, an AI-enabled device is technically capable of identifying problems, analyzing the scenario, responding issues, and environment and monitoring the results post-implementation.
AI which was once seen as the technology to unveil the future has the potential to transmute the core sectors of the software industry. Artificial intelligence is not limited to the technological improvisation, but the technology has also spawned its wings to the QA sector and steadily rooting itself in other processes too.
Why AI in QA?
Quality Assurance is a self-explanatory term that requires no prelude to technocrats. Once the user comes across ‘QA Tested’ label, the user remains assured that the device is perfect. Same is the case in software development, where software is devised to be passed through Quality check after the testing.
AI in QA can be visualized as the robotic procedure of analyzing the SDLC process with precision followed by fixing the bugs. On pilot-scale implementation of AI in QA procedure, the AI was found more efficient than human work-force. It takes few hours to accomplish the week’s work and requires no monitoring as the system itself is complete and independent. The successful implementation of AI proved boon to the QA sector with a counter hostility of burning pockets for being an expensive technology.
How has AI improvised QA?
Artificial Intelligence is a branch of Machine Learning. So, artificial intelligence makes a machine learn the routine processes followed in the QA process. The true potential of the AI to transmute the QA process is massive. AI benefits the automated testing in QA by allowing machines to learn, grasp, analyze and perform intelligent actions on their own and benefitting the software.
? Failure Reduction: Software performance failure is evident until the time it reaches the QA stage where it is fixed by the professionals having years of experience. For instance, they can easily predict the issue in the software along with the situation when they can occur.
AI gives the platform where the machines with humans can automatically fix the issues by employing predictive learning.
? Reduced Testing: Automated testing has evolved the testing procedures. With AI, the QA procedures are getting advance. The technology actively involves human intervention for monitoring, but the technology itself is capable to manage the automated testing related issues. AI bots are being designed to drive the automated tests whenever required, but still, professionals cannot leave the testing methods completely on AI.
? Highly Productive: AI bots are intelligent and are machine dependent with an understanding of its architecture and performance. AI bots assist in reducing false positives drastically and shorten QA regression time analysis to almost three-fourths. Along with maintaining the technical quotient and performance quotient, AI actively participates in delivering the releases to the customers.
? Reduced Miscellaneous Costs: The QA process inducted with AI may prove the boon to your enterprise as it is the unmatched intelligent technology where most of the things are performed without human intervention. To keep the technology running, enterprises have to cough a good amount of bucks.
With the adaptation of AI by some enterprises and its induction in QA process has completely transformed the automated testing process in QA testing. Till now, only the ongoing prospects of the technology are being focused. But, industries have unleashed the potential of the technology for their field and upon implementation fruitful results were obtained.