Source: devops.com
AWS Brings Machine Learning to Code OptimizationCategory: Data, github, machine-learning, artificial-intelligence
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Amazon Web Services (AWS) has made generally available a tool dubbed Amazon CodeGuru that employs machine learning algorithms to recommend ways to improve code quality and identify which lines of code are the most expensive to run on its cloud service.
Amazon CodeGuru is based on a set of AWS machine learning algorithms to identify best practices for deploying code.
Once a pull request is made, Amazon CodeGuru automatically starts evaluating the code using trained artificial intelligence (AI) models developed using data gathered from thousands of different open source software projects by AWS and its parent company. Once the analysis is completed, Amazon CodeGuru will generate a graph showing such metrics as latency issues and CPU utilization rates, as well as human-readable recommendations to surface specific issues and remediations that include example code and links to relevant documentation for any line of code.
Amazon Web Services (AWS) has made generally available a tool dubbed Amazon CodeGuru that employs machine learning algorithms to recommend ways to improve code quality and identify which lines of code are the most expensive to run on its cloud service.
Amazon CodeGuru is based on a set of AWS machine learning algorithms to identify best practices for deploying code.
Once a pull request is made, Amazon CodeGuru automatically starts evaluating the code using trained artificial intelligence (AI) models developed using data gathered from thousands of different open source software projects by AWS and its parent company. Once the analysis is completed, Amazon CodeGuru will generate a graph showing such metrics as latency issues and CPU utilization rates, as well as human-readable recommendations to surface specific issues and remediations that include example code and links to relevant documentation for any line of code.
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