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How Accenture is using Amazon CodeWhisperer to improve developer productivity
CodeWhisperer is powered by a Large Language Model (LLM) that is trained on billions of lines of code, and as a result, has learned how to write code in 15 programming languages. You can simply write a comment that outlines a specific task in plain English, such as “upload a file to S3.” Based on this, CodeWhisperer automatically determines which cloud services and public libraries are best suited for the specified task, builds the specific code on the fly, and recommends the generated code snippets directly in the IDE. Moreover, CodeWhisperer seamlessly integrates with your Visual Studio Code and JetBrains IDEs so that you can stay focused and never leave the IDE. At the time of this writing, CodeWhisperer supports Java, Python, JavaScript, TypeScript, C#, Go, Ruby, Rust, Scala, Kotlin, PHP, C, C++, Shell, and SQL.
In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity.
“Accenture is using Amazon CodeWhisperer to accelerate coding as part of our software
engineering best practices initiative in our Velocity platform,” says Balakrishnan
Viswanathan, Senior Manager, Tech Architecture at Accenture. “The Velocity team was
looking for ways to improve developer productivity. After searching for multiple options,
we came across Amazon CodeWhisperer to reduce our development efforts by up to 30%
and we are now focusing more on improving security, quality, and performance.”
Benefits of CodeWhisperer
The Accenture Velocity team has been using CodeWhisperer to accelerate their artificial intelligence (AI) and machine learning (ML) projects. The following summary highlights the benefits:
- The team is spending less time creating boilerplate and repetitive code patterns, and more time on what matters: building great software
- CodeWhisperer empowers developers to responsibly use AI to create syntactically correct and secure applications
- The team can generate entire functions and logical code blocks without having to search for and customize code snippets from the web
- They can accelerate onboarding for novice developers or developers working with an unfamiliar codebase
- They can detect security threats early in the development process by shifting the security scanning left to the developer’s IDE
In the following sections, we discuss some of the ways that the Accenture Velocity team has been using CodeWhisperer in more detail.
Onboarding developers on new projects
CodeWhisperer helps developers unfamiliar with Amazon Web Services to ramp up faster on projects that use Amazon Web Services services. New developers in Accenture were able to write code for Amazon Web Services services such as
Writing boilerplate code
Developers were able to use CodeWhisperer to complete prerequisites. They were able to create a preprocessing data class just by typing “class to create preprocessing script for ML data.” Writing the preprocessing script took only a couple of minutes, and CodeWhisperer was able to generate entire code blocks.
Helping developers code in unfamiliar languages
A Java user new to the team was able to easily start writing Python code with the help of CodeWhisperer without worrying about the syntax.
Detecting security vulnerabilities in the code
Developers were able to detect security issues by choosing Run security scan in their IDE. Detailed insights on the security issues found are provided directly in the IDE. This helps developers detect and fix issues early.
“As a developer, using CodeWhisperer enables you to write code more quickly,” says Nino Leenus, AI Engineering Consultant at Accenture. “In addition, CodeWhisperer will help you code more accurately by eliminating typos and other typical errors with the aid of artificial intelligence. For a developer, writing the same code multiple times is tedious. By recommending the subsequent code pieces that you may need, AI code completion technologies reduce such repetitious coding.”
Conclusion
This post introduces CodeWhisperer, an AI coding companion by Amazon. The tool uses ML models trained on large datasets to provide suggestions and autocompletion for code, as well as generate entire functions and classes based on natural language descriptions. This post also highlights some of the benefits seen by Accenture when using CodeWhisperer, such as increased productivity and the ability to reduce the time and effort required for common coding tasks. You can activate CodeWhisperer in your favorite IDE today. CodeWhisperer automatically generates suggestions based on your existing code and comments. Visit
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