[Problem Statement]
Develop a Full Stack Web Application for Cast software’s code analyzer.
Code analyzer is the code analysis tool which detects syntax bugs and leaks. You are expected to integrate open source code analyzer tools for different languages in your web app.
[Ideal Behaviour]
On Front End:
— Your web app should provide an editor window where the users can paste their code for the analysis.
— Your web app should ask the user to select the language of the code to analyse.
— Alternatively implement a system to upload the single code file and automatically detect the language of it and start analyzing.
— Show comprehensive detailed analysis of bugs and leaks in a dedicated page.
On Back End:
— All code quality analysis happens on the backend
— Create a RESTful backend that should interact with front end to receive request and render response of the evaluated code
[Plus Point]
— Perform QA testing using the following applications
--Chai
--Mocha
--Jasmin
--karma
— Documented, well structured beautified code.
— Awesome if you could manage to host this application somewhere with Demo URL!
(Amazon aws, firebase, heroku or openshift)
[Extra Work]
— Store all the evaluated code snippets/stubs with accompanying evaluation results in Db.
— Implement a Token based Authentication for login/logout.
— Custom elegant design, fonts and icons to make web app more user-friendly.
— You may add portfolio activity comprising awesome work you have done on web application.
— Use your imagination and add features which would make things easier for end users.
Note: If you complete any or all of the above mentioned levels please do submit.
[Guide]
Static Code Analysis libraries and tools list: https://github.com/mre/awesome-static-analysis
Tech stack:
Front End: Any javascript framework such as Angularjs, Reactjs, Vuejs.
Back End: Java Spring, Go, Python - Django
Database: Mysql or any NoSQL Db.
[Important Note]
Push the working copy of Code Analyzer into github and share us the link to your public repo along with the instruction to install (readme.txt)