Boost your development speed with Amazon CodeWhisperer, an ML-driven coding assistant providing real-time code recommendations in your IDE
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About Amazon CodeWhisperer
Introducing Amazon CodeWhisperer: The ML-Powered Coding Companion to Accelerate Application Development
Amazon CodeWhisperer is a groundbreaking machine learning (ML)-powered service designed to enhance developer productivity by providing automatic code recommendations based on natural language comments and code in the integrated development environment (IDE). It aims to empower developers to create syntactically correct and secure applications faster and more efficiently.
Key features of Amazon CodeWhisperer include:
- First-class support for AWS APIs, making it easier to use AWS services like Amazon EC2, AWS Lambda, and Amazon S3.
- Ready-to-use code customized for individual developers, understanding their intent, patterns, and style.
- Built-in security scans to detect vulnerabilities and provide intelligent suggestions for remediation.
- Code reference tracker to identify similarities with CodeWhisperer training data and provide references for further review.
- Responsible use of AI/ML, avoiding biased code recommendations and fostering innovation.
Benefits of using Amazon CodeWhisperer:
- Accelerated application development with automatic code recommendations.
- Empowerment of developers to create next-gen applications with ML-driven code suggestions.
- Streamlined integration of AWS services with code recommendations for popular APIs.
- Automated unit test generation, saving time and effort in writing repetitive test code.
Areas of use for Amazon CodeWhisperer span frontend and backend development, ML model building and training, and application development using AWS services.
In summary, Amazon CodeWhisperer is a powerful ML-driven coding companion that helps developers create applications faster and more efficiently. Its wide range of features and benefits make it an indispensable tool for modern developers seeking to stay ahead of the curve.
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