How To Use Automation and AI To Become a Better Programmer in 2021
We get to hear of feats achieved through automation and Artificial Intelligence (AI) in almost every field. Software development is no different. AI and automation have found their way into almost every stage of the software development life cycle (SDLC.)
We hear about AI that can write code and conduct testing. Does the existence of these AIs mean that human programmers are becoming redundant? A survey of over 550 software developers by Evans Data reveals that 29.1% fear that their development efforts will be replaced by AI!
While AI and automation are becoming more advanced, this advancement isn’t anything to worry about. Instead of being a hindrance to growth, these systems are here to support programmers and take over menial, repetitive coding tasks, leaving room for the complex tasks that only human programmers can do.
In this article, let’s dive deep into how automation and AI can help you become a better programmer in 2021.
Which AI Applications Can Write Code?
Today, there are a handful of AI applications that are capable of writing code by going through and learning from different databases. Here are a few of them:
- DeepCoder: Developed by Microsoft and researchers from Cambridge University, this AI application is capable of helping programmers solve simple coding problems and coding efficiency over time.
- Commit Assistant: An AI application by Ubisoft that helps programmers detect potential bugs and prevent coding mistakes.
- Diffblue Cover: Helps programmers generate unit tests for their code.
- Microsoft’s IntelliCode: An AI-assisted development tool that helps programmers by making recommendations for code changes. This tool was developed by accessing thousands of open source projects on GitHub.
Now that you know about a couple of the AI applications and their functions, let’s look at how you can actually use them to improve your workflow and overall productivity.
How Automation Actually Helps Programmers
As you might have already guessed, AI applications such as those mentioned in the previous section can be highly beneficial tools that can help programmers save time and focus on more complex tasks.
For example, ask any programmer and they would agree that writing unit tests for their code may not be the best use of their time. Wouldn’t it be wonderful if an AI tool created unit tests for your code while you utilized your brainpower on coding interesting, more useful applications?
Similarly, AI tools that can detect potential bugs or offer useful, more optimized suggestions for your code can also be quite helpful in saving you time. You can use this saved time to create complex application programming interfaces (APIs) or any other complex applications that specifically need a human programmer’s touch.
All in all, automation is really just a tool that allows you to focus your time where you actually want to spend it, taking over the menial tasks while you work on the good stuff.
Involvement of AI and Automation in the Overall Programming Cycle
Knowing why programmers should use AI and automation is only half the battle. The next half is knowing how to use it.
Let's look at how AI is used throughout the overall programming cycle:
Requirements Gathering and Analysis
Misalignment between business requirements and programming can turn out to be a huge loss for businesses. Programmers may need to rewrite the entire code if there are any gaps in the requirements gathering and analysis phase of the SDLC.
Artificial intelligence and automation can bridge this gap with the help of AI-powered tools that can analyze requirements documentation. Such tools are capable of identifying any inconsistencies in the requirements and flag them so that programmers can eliminate any ambiguities in the requirements before they begin coding.
Tools such as DeepCoder, Commit Assistant, and Intellicode can help programmers develop fragments of simple code. The pieces of code created by the AI tools might not be logically or syntactically 100% accurate, but they can save a lot of time and get you out of developing redundant code.
AI and automation tools such as Diffblue Cover can help you with the testing phase of the programming cycle. AI can help you automate the process of generating test cases and running them.
Mesmer is another tool that automates mobile app testing. Such tools can be much more accurate and quicker in finding software bugs in applications and making timely amendments.
Deployment is a tricky process where many things can go wrong. Thanks to AI and automation, this part of the programming cycle can be optimized too!
AI tools can go through prior code releases and deployment logs to warn you of any imminent defects or failures. In case of failures, AI can help you find the root cause for the deployment failure and even help you fix it.
How To Leverage the Ecosystem of “Software Creating Software”
By now, you might be convinced that the fear of AI taking over programmers’ jobs may be too far-fetched and that AI and automation are actually here to help you in your programming careers.
Now let’s go through how you can get started taking advantage of all the benefits AI and automation have to offer.
1. Choice of the Platform
As discussed in the previous section, there are various types of AI and automation tools available to help programmers through the different stages of the SDLC. So depending on your needs and business requirements, you can choose the AI platform of your choice.
Tools such as Diffblue and IntelliCode offer free trials. You can make use of these to check whether these platforms are the right fit for your software development needs.
Usability is another important factor to consider while picking an AI and automation tool for your programming needs. You cannot, of course, expect such tools to be completely error-free. You may need to monitor and review the code written by these tools.
However, you want to make sure that you do not end up wasting more time and energy on proofreading the code than actually developing it yourself without the help of the tools.
You must also ensure that the code adheres to usability standards with respect to your business requirements. For example, an AI and automation tool meant for eCommerce fulfillment solutions should consider the specifications of the eCommerce workflow.
3. Trust Factor
If any AI tool is meant to improve the efficiency of your code and detect imminent bugs, the tool should be reliable and trustworthy enough to work on these areas. The last thing any programmer would want is to discover lots of bugs and defects after deploying the code into production.
As a programmer, you know the importance of security in software development. While picking an AI tool, ensure that it offers the highest level of security so that you can be at peace with the tool accessing your codebase and database.
While developing any software application, giving priority to scalability is always a priority for most programmers. The same goes for the AI and automation platforms. Make sure that there is always scope for scaling the code based on changing business and end-user needs.
AI and Automation Are Here To Help Programmers Rather Than Replace Them
Machines taking over humans might be a good idea for movies, but this is far from the actual reality. The fact is that AI can learn from existing codebases and data fed by you. But what AI cannot do is think like human programmers, drive business decisions, innovate, or develop complex pieces of code.
So you can rest assured that AI and automation are here to help you and not to replace you. Instead of fearing AI, you can embrace and adopt it. Explore the different AI-powered coding tools and how these can help you progress in your career as a top software developer in 2021.