Mouse-click programming has long been a new trend in programming. Simply put, it is a method of coding when ready-made modules of code are being put together to form a new piece of software. It is needless to say that this way of writing programs is far from perfect. To start with, the programmers who do this kind of programming may not even know what is in those modules. This leads to two basic problems: unintentional or intentional bugs, poor code that does not work properly.
The former owes to the fact that the modules might have been written for different scenarios and will lead to slow operation of the program in scenarios that differ from the ones they were written for. This is especially true when it comes to operational load. The latter comes down to the fact that programmers might not look closely enough at the code of a block, which allows for a hidden backdoor that can allow someone to hack the system. And for the lack of appropriate testing, they stay unnoticed most of the time.
Presently, we have such open-source code bases like GitHub, Copilot, DeepMind, AlphaCode. They serve as databases of code that can be used by artificial intelligences to compile their own code.
What can artificial intelligence do here? First and foremost, AI can write tests that will model popular threats through phasing. Secondly, AI can write its own blocks and compile appropriate blocks from code banks that contain thousands of blocks, many of which are not good enough. Ultimately, this will save time and money.
Depending on the AI, sometimes it can write its own optimized code that will be legible and efficient in operation. Such code is easier to work with afterward because it is well-written, which will save time if certain updates need to be implemented in the future. Also, artificial intelligence is much more efficient at researching open-source code in code databases by certain parameters. This allows it to analyze and filter the code fast and employ the best practices to help create operation-efficient code that will be used in the product.
Another problem with software development is a lack of clear understanding of a client and what he needs. Oftentimes, programmers have to explain it as the scope of work and the specificities of the end product lack clarity. Artificial intelligence can allow a client to select the required parameters from a catalog and create a scope of work that will be more understandable for programmers and project managers.
An answer to this question can be bilateral. Artificial intelligence can replace human programmers to a certain degree and in tasks of limited complexity. If you need something simple that can be replicated using existing open-source code databases, you can easily rely on artificial intelligence to write the full code for you. But when it comes to big projects, you cannot rely on artificial intelligence to do all the work for you. In such situations, you can only rely on AI as a supplementary tool but not something that will take charge of the entire development process. It means that big projects will still need project managers and leading specialists supervising the work of UX, frontend, etc. departments.
AI’s intellectual capacity is largely insufficient for solving creative tasks that arise in the process of software development, and it cannot manage the complexity of the creative workload that you need to fulfill to complete a product. But artificial intelligence is certain to raise competition among IT specialists because it will be very able to compete with them at the level of tasks of basic levels, such as using code blocks.