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What is Code Climate?

Velocity delivers comprehensive, context-rich analytics that empower engineering leaders to assist their team members, overcome obstacles, and enhance engineering workflows. With actionable metrics at their fingertips, engineering leaders can transform data from commits and pull requests into the essential insights needed to drive meaningful improvements in team productivity. Quality is prioritized through automated code reviews focused on test coverage, maintainability, and more, allowing teams to save time and merge with confidence. Automated comments for pull requests streamline the review process. Our 10-point technical debt assessment provides real-time feedback to ensure discussions during code reviews concentrate on the most critical aspects. Achieve perfect coverage consistently by examining coverage on a line-by-line basis within diffs. Avoid merging code that hasn't passed adequate tests, ensuring high standards are met every time. Additionally, you can swiftly pinpoint files that are frequently altered and exhibit poor coverage or maintainability challenges. Each day, monitor your advancement toward clearly defined, measurable goals, fostering a culture of continuous improvement. This consistent tracking helps teams stay aligned and focused on delivering high-quality code efficiently.

What is Amazon CodeGuru?

Amazon CodeGuru is a cutting-edge tool designed for developers that employs machine learning to provide valuable recommendations for improving code quality while identifying the most expensive lines of code within an application. By integrating Amazon CodeGuru into your existing software development workflow, you can take advantage of automated code reviews that help highlight and enhance these costly segments of code, ultimately leading to lower overall expenses. In addition, Amazon CodeGuru Profiler aids developers by pinpointing the most resource-demanding lines of code, offering detailed visual representations and actionable advice for optimizing the code to save costs. Moreover, Amazon CodeGuru Reviewer uses machine learning techniques to uncover critical issues and subtle bugs during the application development process, thus improving the code's overall quality. This all-encompassing strategy not only simplifies the development process but also cultivates a more efficient and economically viable coding environment. By leveraging these tools, developers can significantly enhance both their productivity and the reliability of their applications.

Media

Media

Integrations Supported

GitHub
Beanstalk
Betterscan.io
DeepCover
Google Chrome
Jira
Lighthouse
RuboCop
Shift
Slack
Stackreaction

Integrations Supported

GitHub
AWS App Mesh
AWS CodeCommit
AWS Fargate
Amazon EC2
Amazon EKS
Bitbucket
Java
Python

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

Code Climate

Date Founded

2011

Company Location

United States

Company Website

codeclimate.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/codeguru/

Categories and Features

AI Code Review

Not specified

Code Coverage

Not specified

Continuous Integration

Change Management
Continuous Delivery
Continuous Deployment

Data Visualization

Analytics
Dashboard Creation
Filtered Views
Visual Discovery

DevOps

Dashboard
KPIs
Prioritization
Release Management
Timeline Management

IT Project Management

Supports Agile
Supports Scrum

Product Management

Collaboration
Resource Management
Workflow Management

Static Code Analysis

Not specified

Categories and Features

AI Code Review

Not specified

Application Performance Monitoring (APM)

Baseline Manager
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance

Code Quality

Not specified

Machine Learning

Deep Learning
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization

Static Code Analysis

Not specified

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