September 23, 2022
Software testing and quality assurance services at present are crucial processes and are performed in parallel with software development for delivering the best level of quality. Artificial intelligence when integrated with testing services makes it even more efficient. In this blog, we will discuss the benefits and effects of AI and bots when implemented with these testing processes.
Software testing and quality assurance are very important processes and follow effective testing procedures and techniques to make sure that the customer receives the best quality software or application. These processes are a very essential part and are taken up along with the process of software development for delivering the best level of quality and customer delight through flawless application or software development.
At present, with the DevOps and agile practices on the go, the software testing and quality assurance processes have taken a shift-left approach. In this approach, the process of software testing is taken up along with the development, and both of these run parallelly.
Previously, with the waterfall approach, software testing and quality assurance were performed manually and were the last step in the software development life cycle (SDLC). This process being in the last phase of SDLC led to a lot of flaws and bugs, missed timelines of projects, and resulted in extra expenses. But today with continuous improvements, integrations, and continuous deliveries planted in DevOps, software development has taken a shift-left approach as discussed earlier and moved slowly from manual to automated testing.
It was observed that the companies could attain a lot of benefits such as quality products along with faster & continuous releases just by leveraging test automation. Still, their hunt for faster and increased returns on investment and full automation led to the innovation of Artificial Intelligence.
Gradually, the era of automation and smart AI-driven software testing and quality assurance has come into existence. This AI is more like an umbrella term with the latest technologies and a set of algorithms that allow the systems to mimic human intelligence. A wide range of these algorithms is developed using robotics, natural language processing (NLP), machine learning (ML), cognitive computing, computer vision, etc.
It is necessary to note that for software testing and quality assurance, most of the processes are recurring because the software or application features need to be tested many times before launch. It is about giving different inputs and compiling them to check the expected outputs. Such processes stand out to be the best and effective ones for applying machine learning for training purposes of the AI Bots.
AI bots are nothing but AI-powered chatbots being used to stimulate human interaction in the form of chats with the users. Working like humans, these chatbots ensure tasks’ automation, etc. Still, etc. Still, and save a lot of time and costs.
Significantly for AI-powered bots to operate with software testing, one needs to have the goals to be specific and more defined, for use. The software testing and quality assurance team need to be well aware of the functioning of AI to reap all the benefits of AI bots in the process of software testing.
The AI-powered bots are built around NLP and Machine learning algorithms and deliver many loads of benefits when used in quality assurance and software testing.
We are already aware that AI-powered bots can work 24x7. Using this feature, the bots can be put to good use of debugging projects overnights which can be done by expanding the run-time of testing. After this, the testing managers can directly examine the test outcomes and work over the errors.
More developed automation can see self-modification of codes to settle the bugs.
Utilizing AI in robotics for advancing continuous testing can expand the extent of ongoing testing processes. Utilizing AI software testing and quality assurance again and again for performing the grunge work can enhance the quality of testing, hence, enabling the team to work more efficiently and viably on other projects.
A typical issue with software testing is that as a project is being developed, the frequent testing parameters raise the workloads for the team.
But, using AI-powered bots, the testing managers can reconstruct the test for incorporating new parameters and the testing coverage can be raised without the addition of any extra parameters to the workload.
AI in software testing and quality assurance identifies the need for the final result and produces codes for hundreds of tests in a very less time.
AI and bots are no more a buzzword, rather they are today’s reality. The statement is equally valid in software testing and quality assurance services, like anywhere else in this world. The role and benefits of AI and bots in testing are just an edge of what AI is.
If you are wondering about AI and bots implementation in testing, Consagous Technologies is one of the best software quality assurance service providers in testing. Get in touch with us for flawless software testing and quality assurance services.
How Does Quality Assurance Work With AI?
Manual vs. Automated vs. Integrated- What's Best for Modern App Testing?