How To Leverage Artificial Intelligence (AI) In Software Testing?

By Ray Parker

The spectrum of software testing has never been so broad. As of today, APIs are used to connect applications, and they also grow in complexity from one day to the next. So, what can testers do about it? Well, Artificial Intelligence (AI) plays a pivotal role in leveraging automation for software testing. AI may take back the software testing industry, but testers are preparing to mitigate any disruptions on their way. The advent of automation testing is driven by Agile and DevOps methodologies, which calls for robust software products released into the market with speed. This indicates that software testers have progressed in the DevOps environment. DevOps is making organizations accelerate their quality assurance process. automating test requirements is important to survive in the new development environment.

The scope of software testing has also increased as the APIs have improved. APIs legacy systems are used for applications to interact with one another, which in return increases the code suites to increase. With the growth of the software economy and digital transformation efforts, businesses demand a real-time risk assessment through all stages of the software development lifecycle. So, an independent software testing company is considered to achieve the results. ‘

Now let’s see how AI is contributing to companies that are investing in AI:

• AI assists organizations in achieving testing goals by testing ‘smarter’ instead of ‘harder’. AI is a gift to technology that allows computers to learn without any programming. Enterprises can leverage AI to introduce automation by supervised and unsupervised methods.
• AI is leveraged in test automation for object application categories for all user interfaces. Testers create AI-enabled maps that support a graphical user interface (GUI).
• AI-powered testing platforms easily recognize changed controls. These continuous changes in the algorithms will ensure that even slight changes in the codes or algorithms will be identified easily.
• Organizations can also conduct exploratory testing by leveraging AI within the testing suite. It can assign, monitor and categorize risks efficiently. Testers can create heat maps to identify issues in the testing process and also helps in improving test accuracy.
• AI is leveraged to identify issues in application testing, defect and efficiency analysis. Machine Learning (ML) which is also a part of the AI, allows algorithms to test programs and generate test data. With the help of AI and ML, the overall testing process is improved and accuracy is ensured.
• With the help of AI, enterprises can also increase the overall test coverage and scope of tests. These algorithms can optimize the test suite, enhance traceability, etc. AI makes testers' job easier by carrying out repetitive tests on its own and allowing them more time to be creative.

Conclusion

The ultimate aim of introducing AI in software testing is to improve the testing process. Ai has done wonders for software testing and has a lot more to come in the future. It enables quality engineering and reduces the testing required for testers. AI helps in saving time, money and resources for enterprises.

Author Bio:

Ray Parker is a senior marketing consultant with a knack for writing about the latest news in tech, quality assurance, software development and travel. With a decade of experience working in the tech industry, Ray now dabbles out of his New York office.