The machine learning aspect of AI technology promises to be a huge game changer and is already gaining popularity across all industries, and especially so in the software development sector.
Machine learning is currently being used to increase the accuracy of data, improve analysis results and decision-making, as well as massively speed-up multiple phases of the software development process. Developers are also constantly learning new ways to apply it to other areas of software development.
Let’s look at the different areas of software development where machine learning is already having a huge impact.
Code maintenance is crucial to keeping a company’s operations flowing smoothly and evolving the technologies they implement along the way, so a major advantage is that it will give businesses the ability to handle code reviews and refactoring. It is a time-consuming task for even the most skilled coding expert, and there always remains the human error factor to consider. Machine learning provides a much better alternative with automatic code reviews and optimization.
Speeding-Up the Prototyping Process
Developing an idea into a marketable product can take many months due to the various stages involved. After the brainstorming and wire-framing stages comes the prototyping stage, which can add weeks and even months onto the timeframe. Machine learning has the potential to dramatically reduce the amount of time spent on this part of the process. It will also reduce the number of technical experts required to develop and manage the software involved, thus saving significant amounts of money for the firms using this form of AI technology.
Fixing Bugs and Testing Tools
All systems contain bugs due to the huge amount of data they contain as well as the human error factor, but machine learning algorithms can analyze, fix and test for such bugs with only minimal human intervention.
Similarly, testing software becomes a much simpler task from a human perspective when machine learning is involved. It will generate more reliably accurate results and consistently reduce the number of errors even as the volume of data increases.
Increasing Estimate Accuracy
A software development project will be assigned a budget and a deadline once the work involved has been figured out, but such projects are renowned for often going over budget and missing deadlines. Machine learning can use the data from previous projects to provide a much more accurate estimation of both the time required and the total cost.
Improving Strategic Decisions
Just as machine learning can analyze data from past projects to estimate the time and cost, it can help improve the decision-making process when it comes to prioritizing the different aspects of the project. The decisions will be data-driven with minimal risk, meaning development teams can proceed with the project in full confidence that they are on the right track for success.
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