SonarQube: How To Measure Your Code Quality in 5 Easy Steps
18 November 2020 5 min read
SonarQube, developed by SonarSource, is an open-source tool for automated code review and analysis. Consistent code quality is something every manager or technical director aims to maintain, and although new tools pop up frequently, each promising more features than the last, very few code quality and security tools come close to competing with SonarQube. Supporting static code analysis for 20+ languages, this Sonar code quality tool is trusted and used by many professional teams worldwide.
In this article, we will be looking over how to start using the SonarQube tool for code quality in your own projects to generate detailed reports on bugs, security vulnerabilities, duplicate code, code smells, and much more. Let’s get started.
- Can perform automatic reviews with static code analysis for many problems that affect code quality.
- Helps maintain quality and reliability of code projects over its life-span using advanced quality test metrics and graphs.
- Integrates seamlessly with other tools like Jenkins, Atlassian, MSBuild, etc, which helps productive workflow.
How to Use SonarQube Tool For Code Quality:
Step 1: Download and Unzip SonarQube
Prerequisites: Java (Oracle JRE11 or OpenJDK 11 minimum)
SonarQube comes in four different editions, including paid ones, however, for the purpose of this article, we will be using their free open-source community edition.
Click here to download SonarQube Community Edition from their official Downloads page.
After your download has completed, you should find a zip file waiting for you. On Windows, right click and select unzip and double click and extract on MacOS using the Archive Utility.
Also for Linux, you can unzip it using the `unzip` terminal tool.
Step 2: Run the SonarQube local server
At this point, you should be greeted with a little `.bat` file (if you are on windows) or a `.sh` file (if you are on Linux or Mac). The next step will be to execute this file to proceed into the console.
On Windows, navigate into the parent directory containing the `StartSonar.bat` file. This can be done by navigating to the unzipped folder ('sonarqube') and into the bin and windows-x86-xx folder as:
>> cd C:\sonarqube\bin\windows-x86-xx\
Then, run the following command to start the console:
On Mac or Linux, run the following command from your shell terminal:
That’s it! You’ve successfully started the SonarQube local server on your device. You can go to the URL `http://localhost:9000` (9000 is the default port, which can be changed later), and log in using the default credentials:
If you wish to containerize SonarQube, you’ll be pleased to know that the Community, Developer, and Enterprise Editions of the tool are also available as images on Docker Hub as well. Download and start docker container as:
docker run -d --name sonarqube -p 9000:9000 <img_name>
Step 3: Start a new SonarQube project
Now that you have successfully run your SonarQube server, you can proceed to start your first code project. Click on the ‘+’ icon on the top right of the navigation bar and select ‘Create New Project.’
In the next page, enter a unique project key and a short and suitable display Name and click on Set Up.
SonarQube uses tokens to identify you when an analysis is performed. So on the next page, generate a token using any word pair you like (like secret_token or my_token).
After clicking on Generate, Sonar will provide you with a unique alphanumeric secret key. Copy it down, we will need it later for verification purposes. Then click Continue.
Next, click on your OS type (Windows/Linux/macOS) and click on Download. It will link you to a download of SonarScanner. After the download completes, extract the file as in step 2.
Step 4: Setup Project properties and SonarScanner
This step should be pretty straightforward if you have spent any time working on code projects.
directory in your environment variable list. This can be done by adding an entry in the `Add Environment Variables` window for Windows.
On macOS or Linux distros, edit the required Path file to add the bin folder to the system’s environment variable files.
Now we will need to set up a `properties` file for our sonar projects. This is important and we highly recommend that you don’t overlook this step.
On your project folder, create a file named sonar-project.properties and copy-paste the following property variables into the file:
sonar.projectKey=<YOUR_PROJECT_KEY> sonar.projectName=<PROJECT_DISPLAY_NAME> sonar.login = <GENERATED_KEY> sonar.scm.provider =<SCM_PROVIDER> sonar.projectVersion=1.0 sonar.sources=src sonar.exclusions=<EXCLUSION_DIRECTORIES(WONT_BE_SCANNED)> sonar.ts.tslint.configPath=<CONFIG_FILE_.JSON> sonar.typescript.lcov.report Paths=<PATH_FOR_REPORT>
Here we have created our .properties file for our own project, but depending on your environment and path structure, the variables for the properties file will change. Look up the Sonar documentation for property variables related to your project language. Remember that you need to include a sonar-project.properties file on the root folder of every project that you create.
Now open a new cmd shell/terminal on your device and start up the SonarScanner to scan for code quality and security issues.
On Windows, type:
Similarly, run the sonar-scanner shell file using the terminal if you’re on macOS or Linux. If you have followed all the steps outlined in this tutorial, the scanner should start scanning without any problems.
Scanning typically takes a while, depending on the size of the project. Take a moment to relax in the meanwhile!
Step 5: View your analysis report on Sonar Dashboard
After the scan has completed through your code-base, go back to your SonarQube dashboard on http://localhost:9000 and log in using your credentials. Select your created project and you will find a code analysis report waiting for you.
The free Community Edition should include Reliability (measured in # of bugs), Security (in terms of vulnerabilities), Maintainability (depending on your code debt and smells), Coverage, and Duplications. Depending on the number and intensity of each check, the Quality Gate will either 'Pass' or 'Fail' the project. A green color grade will show areas where your code performed well while yellow and red color grades will highlight problem areas.
Furthermore, under the `Issues` tab, you can see the issues in your code, sorted according to intensity. Fixing these will help you and your team increase your quality score.
Give yourself a pat on the back, you have successfully completed a code analysis using the Sonar code quality tool! Now, you can export this report to include it in your presentations or forward it to team managers or other concerned parties.
If you have followed all the steps outlined in this detailed tutorial, you should be able to conduct quality scans for your future projects without any problems. If any error pops up or you want to find certain features in your dashboard or CLI, the SonarQube documentation provides an excellent resource for your problems.
If you need easy set-up and actionable data from day one, try our tool and sonarqube alternative - duecode.io.
- How to measure, check and improve code quality:
Updated on April 21, 2021