What is SonarQube and what are its top alternatives?
Top Alternatives to SonarQube
It is a popular developer productivity extension for Microsoft Visual Studio. It automates most of what can be automated in your coding routines. It finds compiler errors, runtime errors, redundancies, and code smells right as you type, suggesting intelligent corrections for them. ...
It is a provider of state-of-the-art application security solution: static code analysis software, seamlessly integrated into development process. ...
It detects possible bugs in Java programs. Potential errors are classified in four ranks: scariest, scary, troubling and of concern. This is a hint to the developer about their possible impact or severity. ...
Codacy automates code reviews to improve and standardize code quality across large enterprises. It identifies issues through static code analysis. Integrates with GitLab, GitHub & Bitbucket. ...
It seamlessly integrates application security into the software lifecycle, effectively eliminating vulnerabilities during the lowest-cost point in the development/deployment chain, and blocking threats while in production. ...
It is an IDE extension that helps you detect and fix quality issues as you write code. Like a spell checker, it squiggles flaws so that they can be fixed before committing code. ...
It is a free code coverage library for Java, which has been created based on the lessons learned from using and integration existing libraries for many years. ...
SonarQube alternatives & related posts
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We use PMD alongside Checkstyle and FindBugs (Spotbugs) for our static code analysis, as a standard stage in all of our pipelines. PMD offers us insight into various optimization possibilities, best-practice alignment, coding convention compliance and general problems with our code.
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I'm planning to create a web application and also a mobile application to provide a very good shopping experience to the end customers. Shortly, my application will be aggregate the product details from difference sources and giving a clear picture to the user that when and where to buy that product with best in Quality and cost.
I have planned to develop this in many milestones for adding N number of features and I have picked my first part to complete the core part (aggregate the product details from different sources).
As per my work experience and knowledge, I have chosen the followings stacks to this mission.
Service: I have planned to use Java as the main business layer language as I have 7+ years of experience on this I believe I can do better work using Java than other languages. In addition, I'm thinking to use the stacks Node.js.
Database and ORM: I'm gonna pick MySQL as DB and Hibernate as ORM since I have a piece of good knowledge and also work experience on this combination.
Search Engine: I need to deal with a large amount of product data and it's in-detailed info to provide enough details to end user at the same time I need to focus on the performance area too. so I have decided to use Solr as a search engine for product search and suggestions. In addition, I'm thinking to replace Solr by Elasticsearch once explored/reviewed enough about Elasticsearch.
Host: As of now, my plan to complete the application with decent features first and deploy it in a free hosting environment like Docker and Heroku and then once it is stable then I have planned to use the AWS products Amazon S3, EC2, Amazon RDS and Amazon Route 53. I'm not sure about Microsoft Azure that what is the specialty in it than Heroku and Amazon EC2 Container Service. Anyhow, I will do explore these once again and pick the best suite one for my requirement once I reached this level.
Build and Repositories: I have decided to choose Apache Maven and Git as these are my favorites and also so popular on respectively build and repositories.
Additional Utilities :) - I would like to choose Codacy for code review as their Startup plan will be very helpful to this application. I'm already experienced with Google CheckStyle and SonarQube even I'm looking something on Codacy.
Happy Coding! Suggestions are welcome! :)
It is very important to have clean code. To be sure that the code quality is not really bad I use a few tools. I love SonarQube with many relevant hints and deep analysis of code. codebeat isn't so detailed, but it can find complexity issues and duplications. Codacy cannot find more bugs then your IDE. The winner for me is SonarQube that shows me really relevant bugs in my code.
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Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
Our whole Vue.js frontend stack (incl. SSR) consists of the following tools:
- Vue Styleguidist as our style guide and pool of developed Vue.js components
- Vuetify as Material Component Framework (for fast app development)
- TypeScript as programming language
- Apollo / GraphQL (incl. GraphiQL) for data access layer (https://apollo.vuejs.org/)
- ESLint, TSLint and Prettier for coding style and code analyzes
- Jest as testing framework
- Google Fonts and Font Awesome for typography and icon toolkit
- NativeScript-Vue for mobile development
The main reason we have chosen Vue.js over React and AngularJS is related to the following artifacts:
- Empowered HTML. Vue.js has many similar approaches with Angular. This helps to optimize HTML blocks handling with the use of different components.
- Detailed documentation. Vue.js has very good documentation which can fasten learning curve for developers.
- Adaptability. It provides a rapid switching period from other frameworks. It has similarities with Angular and React in terms of design and architecture.
- Awesome integration. Vue.js can be used for both building single-page applications and more difficult web interfaces of apps. Smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.
- Large scaling. Vue.js can help to develop pretty large reusable templates.
- Tiny size. Vue.js weights around 20KB keeping its speed and flexibility. It allows reaching much better performance in comparison to other frameworks.