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Wilson Mar

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This article contains my notes on Static Analysis of code.

SonarQube (abbreviated to Sonar here) improves code quality by scanning source code to identify issues from meaures it calculates. The functionality it performs is SonarQube performs “static analysis” of programming code.

Static Analysis vs Lint

SonarQube’s licensed competitors include PRQA, which uses this illustration to differentiate itself versus lint programs and “bug catchers”.

The value proposition for using static analysis tools versus simpler lint programs is the time and frustration that developers save analyzing false positives, which leads to less usage and thus more lingering defects (“technical debt”).

A summary of what SonarQube finds estimates Technical Debt, which SonarQube tracks over time.


Sonar scans different facets (such as security).

Different languages

Sonar analyzes various languages using plug-ins.

### Sonar for Scala #

http://www.scalastyle.org/ provides a list of ways to use Scalastyle at https://github.com/scalastyle

by 3 people:

  • Matthew Farwell (http://www.farwell.co.uk/ of Switzerland)



is based on a fork of https://github.com/NCR-CoDE/sonar-scalastyle


SQALE Summary Ratings

Sonar calculates a SQALE Rating based on the open-source SQALE (Software Quality Assessment based on Lifecycle Expectations) methodology defined by industry group http://www.sqale.org/. The caluculation is based on inclusion of rules set in the Common SonarQube repository:

  • Duplicated blocks
  • Failed unit tests
  • Insufficient branch coverage by unit tests
  • Insufficient comment density
  • Insufficient line coverage by unit tests
  • Skipped unit tests

Change SQUALE calculations in the plug-in http://www.sonarsource.com/products/plugins/governance/sqale/


SonarQube Analyzers scan code organized into projects.

sonarqube rules fromdoc

Coding standards include:

  • ISO 26262

  • MISRA (Motor Industry Software Reliability Association) was first published in April 2013 to support C99 and C90 versions of the C language, used mostly for embedded software development.

  • JSF

  • HIC++


Customizable Tags provide a way to categorize and filter rules.

Install Enviornment to Run SonarQube

Since SonarQube runs as a server, it’s best to have it run within a VM.

Install Enviornment to Run SonarQube

  1. Install SonarQube using Homebrew:

    brew install scalastyle

This page was written after downloading file SonarQube 5.1.2 created Jul. 27, 2015 from http://www.sonarqube.org/

Most developers prefer to have Sonar look at code before commit into a team repository. Such preview mode runs do not store results in the Sonar run database.

Plugins enable Sonar to be invoked several ways:

  • From a command line as one step in local evaluations. This approach enables one-time parameter configuration for each individual user.

  • From inside IDE (IntelliJ, Eclipse, etc.) as part of code unit development and testing.

  • From a build server (Maven, Ant, MSBuild, etc.) as part of continuous integration/build.

The server uses Oracle or OpenSDK, which requires much more work https://github.com/hgomez/obuildfactory/wiki/Building-and-Packaging-OpenJDK7-for-OSX So please stay with Oracle for now.

MySQL is supported.

Docker and Puppet scripts to build the server ???


  1. Read the documentation
  2. Unzip and start
  3. Analyze projects
  4. Ready to improve quality

Jenkins Configuration

Connection to Jenkins: http://docs.sonarqube.org/display/PLUG/SonarQube+Scanner+for+Jenkins

Client Configuration

http://www.sonarlint.org/visualstudio/ SonarLint for Visual Studio is based on and benefits from the .NET Compiler Platform (“Roslyn”) and its code analysis API to provide a fully-integrated user experience in Visual Studio 2015. SonarLint is free, open source, and available in the Visual Studio Gallery.


This article on July 2016 reported that researchers from NYU found that static scans found only 2% of defects injected by their PDF about their LAVA (Large-Scale Automated Vulnerability Addition).

This is both the fuzz testing” and “symbolic-execution” approaches.

More on DevOps

This is one of a series on DevOps:

  1. DevOps_2.0
  2. User Stories for DevOps

  3. Choices for DevOps Technologies
  4. Java DevOps Workflow
  5. AWS DevOps (CodeCommit, CodePipeline, CodeDeploy)
  6. AWS server deployment options

  7. Digital Ocean
  8. Cloud regions
  9. AWS Virtual Private Cloud
  10. Azure Cloud Powershell

  11. Git and GitHub vs File Archival
  12. Git Commands and Statuses
  13. Data Security GitHub
  14. Git Commit, Tag, Push
  15. Git Utilities
  16. GitHub API

  17. TFS vs. GitHub

  18. Jenkins Server Setup
  19. Jenkins Plug-ins
  20. Jenkins Freestyle jobs
  21. Jenkins2 Pipeline jobs using Groovy code in Jenkinsfile

  22. Dockerize apps
  23. Docker Setup
  24. Docker Build

  25. Maven on MacOSX

  26. Powershell Ecosystem
  27. Powershell on MacOS
  28. Powershell Desired System Configuration

  29. Ansible

  30. MySQL Setup

  31. SonarQube static code scan

  32. API Management Microsoft
  33. API Management Amazon

  34. Scenarios for load