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What Is Static Code Analysis? Types, Tools and Techniques

Static Code Analysis
Posted On: 3 January 2024

What Is Static Code Analysis?

Simply put, static code analysis is the software testing technique used to analyze static application code for errors or flaws. Why is it called static? Because it analyzes or tests applications without executing or running them. This means that application testing occurs without a runtime environment or during production.

Also referred to as static analysis, static code analysis can analyze any codebase to check for any bugs or for compliance with coding rules or guidelines like MISRA. This technique can check for compliance with industry standards like ISO 26262.

What are the benefits of static code analysis? Let’s discuss that next.

Types of Static Code Analysis

Static analysis can be broadly categorized into several types:

  • Pattern-Based Analysis: Scans the code for patterns known to lead to errors.
  • Flow-Based Analysis: Examines the program’s control flow and data flow to identify potential issues.
  • Metric-Based Analysis: Uses quantitative measures to identify code that may be complex or difficult to maintain.
  • Semantic Analysis: This involves understanding the meaning of the code to identify deeper, more subtle errors.

How is Static code analysis done

Static code analysis analyzes the source code without executing the program. Here's how it is typically done:

Selection of Tools:

Choosing the right static analysis tools can change the entire process. It is important to check if they are compatible with the project programming languages and frameworks.

Setting Up Rules and Standards:

Before the analysis begins, it's crucial to configure the tools according to specific coding standards and rules. These standards could be industry-specific guidelines or custom rules that align with the organization's coding practices.

Code Scanning:

The selected tool scans the entire codebase. It parses the code to understand its structure and then examines it against predefined rules and patterns. This process can identify many issues, from simple syntax errors to complex security vulnerabilities.

Reporting and Feedback:

After the analysis, the tool generates a detailed report of the findings. This report includes identified issues, their severity, and often a few suggestions to help solve them. The feedback is typically categorized to help developers prioritize the issues.

Review and Action:

Developers review the report and take action based on the findings. This might involve correcting the code, adjusting the rules for false positives, or refining the static analysis process for future iterations.

Integration with Development Workflow:

Ideally, static code analysis is integrated into the CI/CD pipeline. This integration enables regular and automated code scanning with each build, ensuring issues are identified and addressed early in the development cycle.

How to Choose a Static Code Analysis Tool

Selecting the appropriate static analysis tool is a critical decision in ensuring the quality and security of your software.

Language Compatibility:

Initially, ensure that the tool is proficient in the programming languages used in your project. Whether your codebase is in Java, Python, or any other language, the chosen tool should offer comprehensive support, akin to a collaborator who comprehends every line of code with precision.

Ease of Integration:

The tool needs to be intuitive and user-friendly. Opt for a tool that integrates effortlessly into your development environment, enhancing your workflow.

Customization Capabilities:

Each project has its unique requirements. Select a tool that offers extensive customization options that allow analysis parameters, severity levels, and focus areas to align perfectly with your project's needs.

Collaborative Efficiency:

The chosen tool should not be isolated but synergized with your existing development, testing, and CI/CD tool suite. It should contribute positively to your team's workflow, ensuring seamless integration and collaborative efficiency.

Static vs. Dynamic Code Analysis

Aspect Static Code Analysis Dynamic Code Analysis
Definition Analyzes code without executing it. Analyzes code by executing it in a real or simulated environment.
When it’s Performed Before the code is run. While the program is running.
Main Focus Code quality, security vulnerabilities, and adherence to coding standards. Performance issues, runtime errors, and other issues that only appear at runtime.
Tools Required Static analysis tools (e.g., SonarQube, Checkmarx). Profilers, debuggers, and other runtime monitoring tools.

Benefits of Static Code Analysis

As compared to traditional testing methods, static code analysis provides depth to debugging (or testing) any software code. It can effectively check every code line in any application, thus elevating the code quality.

As compared to manual testing, static analysis tools can also increase the speed of application testing. Test automation tools can detect defects (or problems) in software code early in the development phase. Static analysis tools can also pinpoint the exact location of the software bug, thus enabling faster resolution. Moreover, with early detection of minor issues in the SDLC, it takes less testing time and effort to fix them (before they grow into critical bugs).

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The Static Code Analysis technique is less prone to human errors (unlike normal testing methods). This technique is also compliant with global coding standards, thus ensuring high code quality.

Among the major benefits, static analysis tools can easily detect security-related vulnerabilities within any application code. Some of these vulnerabilities can lead to successful cyberattacks like SQL injections and Cross-side Scripting (or XSS) attacks.

Furthermore, static code analysis is easy to perform in any development environment. As this technique only tests the application code, it does not require a runtime environment, thus saving both time and cost. Static code analysis is also easy to integrate with any DevOps or CI/CD workflow. As a result, application developers can focus on fixing code-related problems in any environment.

Limitations of Static Code Analysis

Static code analysis has its share of limitations in application testing. For instance, static analysis tools can report a high number of false positives and negatives. False positives are generated when this technique detects code vulnerabilities that do not exist. On the other hand, false negatives are reported when static analysis does not report code vulnerabilities (that do exist).

Among other limitations, such tools cannot always determine the developer’s intent from the written code. Similarly, the analysis can fail to enforce coding rules that are not applicable to static code. At other times, coding rules (or standards) are based on external documentation or are open to interpretation.

Additionally, it has limitations when it comes to detecting security vulnerabilities like user authentication, access control, and cryptography. Despite some latest developments, static analysis tools can only report a low percentage of security flaws.

How does it perform when compared to dynamic code analysis? Let’s discuss that next.

Conclusion

To sum up, static code analysis effectively detects code vulnerabilities early in the SDLC. As a result, it ensures faster resolution and better code quality. Moreover, it serves to decrease technical debt, increase development productivity, bolster data security, and enhance visibility.

Notably, static code analysis could work wonders with automated tools at disposal. Favorably, with its innovative Test Automation platform, ACCELQ has enabled its customers to improve their test performance and reduce their costs. We can provide the right consultation services on how to implement your software testing.

All in all, we can help you implement automation testing for your applications. Sign up for a personalized product demo today!

Geosley Andrades

Director, Product Evangelist at ACCELQ

Geosley is a Test Automation Evangelist and Community builder at ACCELQ. Being passionate about continuous learning, Geosley helps ACCELQ with innovative solutions to transform test automation to be simpler, more reliable, and sustainable for the real world.

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