Emerging Trends Of AI In Performance Testing

Before a software application is released in the market, it has to be evaluated for speed, scalability, and stability under various load conditions. An application should never go live if it has poor usability. Performance testing ensures an app meets the criteria for its robustness under a certain load. It becomes imperative to understand an app and make it a part of unit testing. Testers set realistic goals and understand users’ perspective and implement DevOps for making their performance testing efforts effective.

AI used to alter manual testing procedures

Previously, performance testing was run by a group of testers into a room and set up test environments, run scripts and then get results. It was a daunting process but automation has greatly served testing processes. As Artificial Intelligence (AI) takes over all the industries, it has a lot to offer in the software development process. It has altered testing processes by automating significant components of the manual testing efforts. AI has improvised with automation where scripts run according to schedule or command. It has not been able to eliminate the need for manual testers, as they were required for result evaluation. There is still time for AI to introduce decision-making capabilities, where manual testing techniques will no longer be required, or its percentage will be too low. However, organizations are leveraging their software testing efforts and considering a reliable performance testing company.

AI Analyzes Test Data Faster

Test data is not only used to gather results from testing activities, but it is also used to test the load it will deploy on a certain software application. For instance, when testing a URL using a lean HTTP request, there is going to be a lot of side data. There are several server requests between data log access and data emitted from within the web server, along with results data. All of this data can be used to provide insights into performance testing. AI can address this issue by optimizing data processing. Humans will set the data-parameters and automation will take over testing data and getting results from it faster than before.

AI will be able to predict bugs and system malware

Software testing can be quite interesting and easier with AI. AI can predict what type of bugs and system malware can be expected to appear in the software development process. The ability to anticipate problems appearing in a system can prevent any unforeseen issues in app development.

Conclusion

We know how important performance testing is to ensure an app’s robustness and functionality. There are different companies that offer performance testing services for various applications. Whether you have a retail app or mobile banking app, performance testing is essential to success in the market. AI takes performance testing to a whole different level. It allows test automation to move past a task executing it without any manual intervention. We also expect AI to automate more testing processes where the need for manual testers is quite less.

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