A lot of people believe that software developers and other jobs related to computer science will be taken over by AI. A survey conducted by Evans Data Corp showed that 1 in 3 software developers believed that their jobs would be replaced by AI.
We need to remember that AI is just Math. It’s just linear algebra, statistics and calculus put together to get machines to mimic human behaviour. This Math helps us predict, classify and do many other tasks that would take a lot more time for a human to do.
If we look at software engineering or software development, we find that it does not just include tasks. The idea of software engineering is to take business problems and break them down into solutions that can be expressed in code, thus building software that can solve those problems. AI and Machine Learning have influenced the Software Development Life Cycle (SDLC). Owing to AI, today programming is not stuck in if-else cycles. AI helps to choose the correct data that can solve a problem without human involvement. AI tools are assisting software professionals to write better code, automatically detect bugs and other safety issues.
Role of AI in developing better software
- Gathering Requirements: This stage of the project consists of collecting, verifying and monitoring what the end consumer wants from a software. Though this sounds easy, it is one of the major causes of delay or failure in software development projects. AI techniques like Natural Language Processing (NLP) help to automate this process by identifying errors such as insufficient information, loopholes, faulty values and accelerate review. Thus digital assistants powered by AI scrutinize the documents, identify inconsistencies and propose improvements.
- Designing: Deciding on the capabilities and characteristics that are to be included in the product takes a lot of time. It is not uncommon for both parties to dispute over this phase after the product is developed. An AI-powered solution that learns from previous software development projects can scrutinize the present software to find the appropriate solution that fulfils all conditions. Based on the user reviews of similar solutions, it can suggest the best factors that can enable this software product to succeed.
- Automatic Coding and Bug Detection: Converting a business idea into code from the ground up, is an arduous task. Here, AI-powered programs can come to the rescue. These tools complete the code and provide suggestions while typing. They work just like Gmail’s Smart Compose feature that proposes words while users type the email. We also have AI tools that automatically identify bugs and propose changes in the code. In other words, AI diminishes the workload to a great extent.
- Testing: Developers have been using automated testing tools for quite some time now. AI takes this up a notch. Along with automatic testing, it generates automatic test cases and can even predict the results without actually conducting the tests. They help to save time, detect flaws and pinpoint the basic cause of those flaws.
- Deployment: Deployment failures can cause huge financial losses. Artificial Intelligence can prevent these failures by predicting them beforehand. They make these predictions by analyzing statistics related to previous releases.
We’ve seen how AI influences the SDLC. The demand for AI-augmented tools for software development is rising as enterprises look for ways to improve the productivity and quality of their developers. AI helps professionals without instruction in software engineering to develop applications. So does that mean the end of software developers? Not really. Their jobs would evolve to include more of machine learning and less of single specific tasks. Instead of replacing developers, AI can help them to create better software by reducing errors, improving security, enriching developers’ skills and reducing time to market the software products.
