AWS Code Guru — Salvation to your Code
A Guru which can guide your code to its ultimate salvation a bug-free world. AWS launches its smartest ML Powered service which will review your code and jolt down recommendations.
AWS Code Guru being a smartest and provides intelligent recommendations for improving code quality and identifying an application’s most expensive lines of code. It comes in two variants. Code Reviewer and Code profiler.
Let me show you how you can reap maximum benefit and set up for your project.
AWS Provides sample git hub repo to play with. So open your personal git hub repo and fork this project into your account.
Once you have done, open your code guru dashboard. Click on Getting started drop-down and select CodeGuru Reviewer as you can see below.
Now select proper source provider, Since I have my code in Git Hub, i have selected Git Hub and click on connect to Github.
A pop up may appear and you will be asked to validate your git hub credentials. Once you allow GitHub to connect to AWS you're are all set to go.
Now select your repo which you intend to scan. and Click Associate Button.
You should be able to see this repo under the associated repository tab.
Click on the name code review in the below menu.
Click on Repository analysis tab. and click on Create repository analysis button.
Select your repository and branch name and click create.
and now you're done. you can see the recommendation.
Code Guru has published 4 recommendations using machine learning to identify critical issues and hard-to-find bugs during application development to improve code quality.
As per AWS Documentation Code Guru is capable of
Detect deviation from best practices for using AWS APIs and SDKs.
Flagging common issues that can lead to production issues, such as detection of missing pagination or error handling with batch operations.
Detects concurrency issues such as atomicity violations and the use of classes that are not thread-safe, which are difficult to find even for experienced programmers. It
Detects when resources are incorrectly closed, creating resource exhaustion and outages.
Identifies a lack of input validation, where unsanitized inputs can lead to issues such as injection attacks or denial of service.
