Artificial Intelligence (AI) is changing all kinds of business functions and the software development industry is no exception. Aside from making the traditional custom software development lifecycle faster, machine learning techniques offer a new paradigm when it comes to inventing different kinds of technology.
AI Creates Better Services
These days, enterprises want to offer their target customers highly-personalized and customized services. To do this, they need the functionality that AI can feed into their software. There are already countless examples of AI building new functionalities and improving apps, whether it’s the bots that write simple news articles or the predictive text you use on your smartphone.
AI Helps Developers and Testers Build Improved Software
Thanks to AI, developers can code better, and QA experts can test software more efficiently. Through this, and machine learning being used to test software, the quality of custom software development is constantly seeing significant improvement. In fact, there are testers that already use bots to look for software bugs.
On the other hand, there is an emerging area focusing on testing tools that can use AI to search for flaws in the software. The same AI can automatically fix the code right after finding a bug.
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AI Speeds Up Strategic Decision-Making
Developers generally go through a long and tedious process when deciding what features should be included in a certain product. This is completely transformed by a machine learning AI solution, which is trained on past development projects and business factors. It has the capacity to analyze how existing applications perform and help both business stakeholders and development teams cut risk and maximize impact.
Changing business requirements into technology specs normally takes a significant timeline in terms of planning. With the help of machine learning, development companies can deliver the product in less time than it would usually take while also increasing revenue.
AI in GUI Testing
Graphical User Interfaces (GUI) are important for interacting with many kinds of software. They are critical systems, so it’s essential to test them in order to avoid potential failures. Unfortunately, GUI testing can be difficult, given that there are only a few tools and techniques available to help with the testing process.
There has been mounting interest in GUI testing with the assistance of AI, and a previous examination concerning how AI would handle GUI testing. A quick look at the ACM library should show that different forms of this system have been used. In some procedures, GUI was created in lieu of a model, while other tests were made in view of a model.
Software development is undoubtedly becoming more complex than ever. This is a positive sign, as more tools are emerging to help developers with all sorts of custom software development projects. With the rise of big data and cloud technologies, AI is sure to be on the radar of many growing companies. It’s also expected to be used more frequently as businesses strive to be one step ahead of the competition while they continuously innovate.