We aren’t going to discuss the main benefits of artificial intelligence and machine learning in this post. It goes without saying that both tools significantly change the world today. Moreover, machine learning became an integral part of our life! Let’s see how it can change software development.
What Is Machine Learning?
Machine Learning or ML is a powerful technology that uses Artificial Intelligence to develop computer software that can “learn”; gradually, the system improves its performance. The main goal of ML algorithms is to train the software. They study and analyze the data. Based on this information, they can identify patterns and gradually make predictions. They can be subdivided into a few groups: controlled, uncontrolled, and semi supervised machine learning algorithms.
Now, let’s move on to discussing a broader topic. Let’s see how ML can change software development. Experts say that ML will undoubtedly transform this industry.
ML Can Find Deviations from Coding Guidelines
The thing is that properly-written software must comply with functional and non-functional demands. Furthermore, it must follow specific coding guidelines. Developers have software development practices and guidelines that they need to follow while building programs and mobile apps. But how can you check if your software development team follows all these guidelines? This is where the use of machine learning might come in handy. In this case, machine learning tools are used to find these deviations. This can positively influence your software development.
ML Makes Software Development Easier
Managing a software development process is a time-consuming task that requires specific skills and experience. Project managers have to deal with a variety of complicated tasks like monitoring the project status, controlling risks, managing quality, or estimating the cost. All this takes time. Project management tools powered by ML allow project managers to control this complexity. They use external data, and organizational information repositories that enable project managers to control risks. Moreover, these tools are also used to build network diagrams, breakdown structures, etc. When ML-powered tools are used, project managers can be more productive.
ML Makes Testing and Code Review Faster
Use ML-Powered Tools to Gain Actionable Insights
If you are a senior developer, you probably know that it is difficult to organize the work of the whole team. You need to set priorities, understand the capabilities of your team, set up communication channels, and make sure the work of IT consultants aligns with the general enterprise strategy. If you don’t want to go crazy, you have to take some measures to simplify all these processes. This is where the use of ML-powered tools might come in handy. It allows you to study the code on repositories and gain practical insights.
As we can see, there are numerous ways in which ML can influence software development. However, it is not easy to develop such ML-powered solutions. What is the future of ML tools? This is the question of major concern for experts working for Google, Amazon or Apple. But it is obvious that we’ll see more programmers that will be using pre-trained models for common tasks very soon. However, there is one thing that makes ML algorithms distinct from standard software development. The thing is that they are probabilistic. You may choose the best models, but even the most accurate model can be wrong. This means that it is not the right tool for solving all the problems.
However, machine learning is meant to change all the concepts of software development fundamentally. Though it presents some real challenges to our old programming paradigms, it is clear that software development will evolve into something different in the near future. We’ll see more tools that are focused on satisfying web and mobile users.