Static code analysis is the process of analyzing the source code of software. This analysis is performed as a review process before the code is compiled or executed. Static code analysis is used to identify the structure, style, errors, defects, security vulnerabilities, and performance issues in the code.
Static code analysis is carried out using automated tools or software platforms. These tools scan the source code, calculate code metrics, and check whether the code conforms to specific rules or best practices. They can also perform functions such as error detection, identifying defects in the code, detecting potential security vulnerabilities, evaluating code quality, and finding performance issues.
Bug effects: Possible errors, logic errors, or pieces of code that do not follow certain rules of the language are detected. This helps to study errors that will arise during operation.
Flaw detection: Identifies areas of code that are difficult to maintain or malicious applications. The readability of this code is increased and it is made more maintainable.
Vulnerabilities: Potential vulnerabilities, pieces of code, or vulnerabilities that could lead to malicious attacks are detected. This helps augment the software’s instructions.
Performance values: Code fragments that cause performance speeds are identified and more effective or optimized code alternatives can be offered.
Code quality configurations: Compliance with code editors or best practices specified in software projects is checked. This allows us to build a code database and develop better-quality software around here.
Why is SonarQube used?
The SonarQube server can test and analyze 29 popular programming languages, from Python and PHP to Kotlin and Swift. With SonarQube, your developers can ensure source code quality and application security by identifying and rectifying code duplications and potential bugs. It also offers different integration options and can be integrated into CI/CD (Continuous Integration/Continuous Deployment) processes
SonarQube helps you find:
Code smells: Identifies maintainability issues.
Bugs: Detects potential errors in code.
Vulnerabilities: Highlights security risks.
Code coverage: Measures unit test coverage.
Duplicated code: Finds duplicate code blocks.
Code complexity: Analyzes complexity metrics.
Technical debt: Assesses the cost of fixing issues.
Compliance: Check adherence to coding standards.
SonarQube code analysis report.
Here, I've broken down each metric (ideal value in brackets) as a quick byte.
→ Code Coverage Percentage (> 80%): Ensures a high proportion of your code is tested, reducing bugs. → Technical Debt Ratio (< 5%): Measures how much code needs refactoring for maintainability. → Number of Bugs (Ideally 0): Counts coding errors needing fixes for functional integrity. → Security Vulnerabilities (Minimal): Identifies potential security risks needing attention. → Code Smells Count (Minimal): Detects 'smelly' code that may need improvement for better readability. → Duplications Percentage (< 3%): Highlights repeated code blocks that should be simplified. → Security Hotspots Reviewed (100%):Ensures all potential security risks are examined. → Complexity Metrics (Cyclomatic Complexity < 10): Evaluates how complicated the code is, aiming for simplicity. → Coding Rules Compliance (Close to 100%): Shows adherence to set coding standards for quality.
→ Quality Gate Status (Passed): Indicates the overall health of the codebase, based on set criteria.
SonarQube is an open-source platform for software quality and security. It is used to detect and analyze errors, flaws, and vulnerabilities in code that occur in software projects.
SonarQube provides various metrics and statistics by doing source code analysis. With these analyses, you can evaluate the quality, maintainability, performance, and security of the code. It is an essential tool for understanding and improving the code base, especially in large and complex projects.
What is SonarRunner?
- SonarRunner (now deprecated, replaced by SonarScanner) is a command-line tool that was used to run code analysis for SonarQube. It scans the code and sends the results to the SonarQube server for review.
You can follow the steps below to start code analysis of your projects
Before we initiate the demo we’ll be conducting, the first step is to prepare the necessary tools. At this stage, we can download the SonarQube Community version that we’ll be using onto our computer.
https://www.sonarsource.com/products/sonarqube/downloads/
Once we have the downloaded file for installation, within the "bin" directory of the downloaded package, we'll find the appropriate "sh" or "bat" file that matches our operating system. Running this file will initiate the installation process and set everything in motion.
SonarQube\bin\windows-x86–64
After the “bat” file runs successfully, we can then establish control by accessing “localhost:9000” through our web browser.
We begin by providing the necessary project details for the code analysis.
We proceed by selecting the repository information for the code analysis.
After choosing the environment in which we’ll perform the build for code analysis, we can use the generated token to execute the necessary commands. By utilizing this token, the appropriate platform for the project’s code analysis will be accessible.
Upon executing the required commands, the project’s code analysis should generate outcomes that are reflected in the displayed interface of the appropriate platform.
The analysis results can be examined on the dashboard, allowing for a review based on the priority status.
Upon completion of the code analysis, the subsequent steps can be displayed, showcasing either the fixes that need to be made or informative messages for guidance.
