prags-mugunthan

As a developer or business owner, you may argue that you don't need “intelligent” software to tackle the tasks of today's technology — especially if it means building high-cost and critical applications. The truth is, with the arrival of artificial intelligence or AI software tools, you can cut down on the duration of the entire software development process significantly.

The typical coding process looks like this: write code, test it, iterate, iterate, iterate and finally — deploy the code. Depending on the type of application, it could take between 2 to 9 months to build one. However, with the help of such tools, developers can automate time-consuming tasks like code compilation, debugging, and code-driven testing.

When it comes to software development, 2 truths seem obvious but feel hard to grasp: time is money, and less is more. When it comes to projects done by AI, we get to experience both of these truths at the same time. When computers do the grunt work for us, we can save time and create more.

This article will discuss 15 AI software tools that can generate code and help you ship your next application in no time.

OpenAI’s Codex

Codex is an AI system built by OpenAI and used to power Github's AI-powered programming tool, CoPilot. It enables the user to translate natural language into code — in several programming languages. The model is trained on natural language and code and is the most proficient in Python with additional capabilities in JavaScript, Go, Perl, Ruby, etc.

Source

Previously, it was only available via CoPilot. Still, the private beta option allows other developers to build their automated programming tools on top of this, or integrate with this system.

Github’s CoPilot

Github’s CoPilot, also known as an AI pair programmer, is created based on OpenAI's Codex. It's trained on billions of lines of code available online and turns any natural language prompt into code. You have to give your input and tell the tool what you want to create — and it'll do the rest of the work for you.

Source

That said, you still have complete autonomy over the code and can edit it to your liking. It's the right option if you're looking for an open-source completion tool.

Tabnine

Tabnine is an AI-completion coding assistant that helps you easily create whole line and full-function code completions. The tool is available on both, cloud and server versions making it user-friendly. Plus, the tool is trained in multiple languages like JavaScript, Python, Go, Bash, etc.

Source

One of the biggest advantages of using Tabnine is that when you keep using the tool, it learns your coding patterns and preferences and starts offering suggestions based on what you prefer. It makes it an indispensable AI programming tool for any software developer.

Intellicode

Intellicode is created by Microsoft and comes integrated with its own IDE, Visual Studio. It provides AI software coding assistance and supports languages like C# and XAML, but it's also compatible with Java, Python, JavaScript, SQL, C++, and TypeScript. It's known to give smart suggestions based on the code and context of the query — partly due to the fact it's trained using half a million of Github's open-source projects.

Source

Amazon CodeWhisperer

Amazon's CodeWhisperer is an ML-powered (machine learning) software tool that helps developers improve their productivity by generating code. In addition, it helps them by providing suggestions for writing comments and gives multiple options to select from before proceeding with the entire code generation process. It only currently supports Java, Javascript, and Python — accessible via the AWS toolkit.

Source

CodeT5

CodeT5 is an open-source AI software for programming created by the team at Salesforce. It's trained based on Google's T5 (Text-to-Text Transfer Transformer) framework — hence, the name. The core audience is Apex developers and there are 3 ways in which it stands out from the rest of its competitors in the market:

• Text-to-code generation — convert natural language to code
• Code autocompletion — insert target function name & generate code
• Code summarization — summarize code in natural language

Source

Polycoder

Polycoder is a direct competitor to OpenAI's Codex — developed by researchers at Carnegie Mellon University. It's an open-source tool available via the MIT license based on OpenAI's earlier model, GPT-2. The software is written in C++ and focuses only on the C family of languages. It's perfect for devs looking for a free, open-source tool to speed up the code generation process.

Cogram

Cogram is a Y-combinator-backed startup that created an AI-powered coding assistant for data scientists and Python programmers. This tool is for you if you're a developer who uses SQL queries and Jupyter Notebooks.

Devs can write the queries in English and the tool translates them into complex queries considering that it's context-aware; it keeps learning and improving with time. You can query databases without having to write the corresponding SQL queries yourself.

Source

Clever-Commit

CLEVER (Combining Levels of Bug Prevention and Resolution techniques) is a combined effort from Ubisoft and Mozilla — focused on identifying bugs in your code. It's one of the few tools that hones this aspect of the software development process. The AI bug-tracking software uses data from its codebase and bug tracking system to pinpoint these errors — automating the debugging process.

Source

Kite

Kite’s AI-powered code completion tool helps developers write their code in Python primarily, but also offers 15 other languages like Kotlin, Java, Go, Scala, and more. On average, it reduces the number of keystrokes by 47% — increasing the dev’s output in a shorter period.

It's available in 16 editors now, making it accessible to a broad audience. You can find files related to the current coding files with ease and also look up Python docs while coding — saving you time spent on gathering your research.

Source

PyCharm

PyCharm is another programming tool based on a Python integrated development environment (IDE). It's one of the most intelligent tools in the market due to the number of features it offers such as:

• Smart code completion
• Code inspection
• On-the-fly error highlighting
• Automated code refactoring
• Cross technology development

With these features, the software can help you complete your code accurately, identify bugs in real-time, and give you everything you need to develop your applications using Python.

Source

Codiga

Codiga is an AI-coding assistant that focuses on helping developers create better code faster. Devs can create, share or reuse code snippets based on their preferences within their IDE like VS Code, JetBrains, and Google Chrome. By helping them share code as and when they need it — collaboration becomes much easier due to its availability on different devices. Many users even indicate that it's almost like having a Senior Software Engineer review each pull request — increasing the accuracy and quality of the code.

Source

aiXcoder

aiXcoder is one of the few code completion tools that demarcates its value from a human developer — with a tagline stating "Leave Artificial Intelligence to AIXcoder. Leave Real Intelligence to Humans." It works based on deep learning model compression techniques that you can use to create a custom code generation and completion tool for your company. One of its standout features includes an offline version helping devs work without distractions.

Source

Sketch2Code

Sketch2Code, a Microsoft product, is a web-based product that uses AI to convert a hand-drawn design into HTML code. This software-as-a-service (SaaS) solution first detects the design patterns using object recognition, then passes the detected elements through a text recognition service and understands the entire structure. Based on these elements, it generates a valid HTML code — allowing developers to visualize their ideas in no time.

Source

Embold

Embold is a multi-dimensional analyzer used for software development projects. The idea behind it is that dev teams shouldn’t waste too much time increasing their technical debt — instead, they need to prevent errors from happening in the first place. Dev teams can review code using automated workflows. Plus, it enables them to review code quality without implementing the change via pull request and commit scans — increasing the accuracy of the deployed code.

Source

Conclusion

As your experience with these tools increases, you'll likely appreciate how useful they are in improving the speed and efficiency of code development. Ultimately, it's up to the developer to decide which tool is best for the job. Some may prefer existing tools they can customize rather than learning a new one. Others may like saving time and effort by using a single standalone program that does everything for them. Ultimately, both have positive aspects, so it's up to you to decide what will work best in your development setup.

If you’re looking for software vendors to help you build your next application from scratch, check out vetted vendors on our website.

FAQs:

Q1. What are 5 AI applications?

With respect to AI software that can help with programming, here are our 5 picks:

• OpenAI’s Codex
• Github’s CoPilot
• Tabnine
• Intellicode
• Amazon CodeWhisperer

There are many applications for AI, and it differs based on the use case and industry vertical. No software can meet the needs of all businesses, so it's best to choose based on your current workflows and what kind of business transformation you expect.

Q2. What is AI software development?

Artificial intelligence allows companies to develop software faster by automating routine tasks. Companies can use AI-powered tools to gain valuable insights into customer behavior and test the code for security holes before releasing it to the public. For example, developers can code using AI software and then test the code using similar tools — drastically reducing the overall development time.

Q3. What coding language is used for AI?

Many coding languages are used to build AI-driven models and applications, but currently, these are the most popular coding languages used for this purpose:

• Python
• Java
• Julia
• Haskell
• Lisp
• R
• JavaScript
• C++
• Prolog
• Scala