AI and Machine learning continuous to be one of the most discussed technologies of all time. Unlike other fads that come and vanish, AI is definitely impacting human lives in many ways in the form of machine vision, smart predictions, autonomous cars etc
But, can Machine Learning accelerate the development of bespoke software and enhance the whole Software Development Lifecycle? AI can be applied to many areas in software development to make the process more efficient and faster. A 2016 Forrester Research survey, reveals that AI can even write code!
Here are some ways in which AI will improve bespoke software development.
Ideation and Planning
If you’ve been in the role of a Software Project Manager, you know how challenging that job is. Identifying product requirements properly from the stake holders, translating them to user stories and developer tasks, accomodating changes in requirement without breaking existing features.. The list goes on.
A study reveals that, 75% of custom software development projects either fail, exceed bugets or miss deadlines.
This is where Machine Learning can help. By analyzing data from several past projects, we might be able to build an automated system that translates requirements, or wireframes to actual user stories and developer tasks, and even assign them to right developers, which can reduce the project planning time by a huge extent.
Also, by analyzing previous data, a deep learning system can estimate tasks, where humans often make mistakes, and it can even predict risks and delays.
Design and Development
This is the major phase in SDLC life cycle, where human talent cannot be simply replaced, as it involves creativity and several other abilities which require human brains.
But still, we can see the growth in No-Code/Low-code platforms which significantly reduces the time in building applications.
Such platforms will continue to emerge and with Machine Learning, they’ll be more powerful enough to develop even enterprise applications without the need of a developer writing code from scratch.
However, we’re still years away from building such an AI system that can build a custom applications without human developers.
This is another area where AI is already making a huge impact. Manual Software Testing is time consuming, and with Agile methodologies, doing continuous testing is not always practical.
Machine learning can do code reviews by analyzing several thousands of opensource code bases available on the web. By pattern recognition, an AI system can predict and suggest improvement for a codeblock, and even auto-correct buggy code.
This will speed up the debugging process and human QA analysts can focus on testing the general usability (UI/UX) aspects of the software instead of trying to find and report functional / syntax errors.
Once AI completely automate test case preparation and testing process, the delivery time and quality of software can be significantly improved.
Even though we’re still far away from building fully automated software development systems, We can be sure that AI will play a massive role in the way how we develop software in the coming years.
How do you think AI will impact software development? Let us know in the comments!