Ivan Homola, Author
Indie maker with a passion for SEO working on web projects. Ex-mobile dev-agency owner. Now, helping early stage founders turn their side projects into businesses.
When it comes to software development, static code testing is the best way to avoid bugs and application security issues.
It helps in the identification of potential security vulnerabilities before they become issues.
In addition, it can help improve quality assurance by providing feedback on coding conventions and maintainability standards.
This guide will teach you the six best practices which you can use to perform static code testing.
1. Run Security Checks
You can run these checks for system and component vulnerabilities to prevent security threats during software development or deployment.
It helps software developers identify and fix security flaws in their code before it gets released. As a result, it ensures the software is secure for users before you deploy it to production.
You can also use it to detect and patch vulnerabilities in existing software applications and systems, reducing the risk of a malicious attack or data breach.
Codiga has a static application security testing feature to find Mitre CWE, Top 10, and OWASP Top 25. Not only that, but it can also find and suggests fixes for major vulnerabilities.
2. Enable Code Standards
There are several benefits of enabling code standards inside any static code analysis tool. Some of them are given below:
Increase code quality
Enforcing code standards helps ensure consistency and overall codebase quality.
Following a consistent set of coding standards makes it easier for developers to read and understand the codebase, which can help reduce the time needed for debugging and maintenance.
Reduce development time
Developers can more quickly fix issues as they arise, leading to faster development cycles.
Having a set of defined standards also makes it easier for new team members to get up-to-speed quickly on an existing codebase, as they can quickly pinpoint where certain functionality is located within the project.
Codiga has a dedicated dashboard to monitor your code quality score.
Some highlighting features are:
- The health score of the codebase.
- Technical Debt
- Equivalent Engineering Effort
- Cost Breakdown
- Remove Defect
- Refactor Duplicate Code
- Reduce Complexity
- Improve readability
3. Detect Dependency Issues
Static code testing can help determine potential problems such as incompatible or outdated libraries, missing files, or incorrect configurations by detecting any dependencies issues. In addition, it can give feedback that the code works correctly and efficiently when deployed in production.
Identifying these issues early can save time and resources by preventing costly rollbacks or rework after deployment.
You can efficiently scan and detect outdated dependencies for your codebase with Codiga's dependency scanner.
4. Turn ON CI/CD
Enabling CI/CD inside your static analysis tool can increase the effectiveness of software testing and development.
It helps to automate the process of running static code analysis, which increases the speed and accuracy of code reviews.
Automation reduces manual efforts and common human errors.
It also allows for faster implementation of code changes, making development more rapid and efficient.
Additionally, it can automatically trigger alerts when you violate specific standards or compliance rules.
You can use Codiga to perform CI/CD (GitHub Actions, Circle CI, AWS Code Build) and connect with GitHub, Bitbucket, and GitHub. Then, import your code repository and get real-time feedback on pull requests.
5. Write Custom Static Analysis Rules
There are many benefits of writing rules to verify that the code meets the requirements and functions as expected.
Writing custom rules allows you to tailor the testing process to your needs.
It gives developers more confidence, and they can be sure that their code will stick to the custom standards.
It also helps with a better user experience and reduces the possibility of introducing errors or bugs into the system.
You can create custom rules with Codiga and access them directly inside your IDEs or CI/CD pipeline.
6. Execute Performance Testing
Performance testing measures the system's performance under various loads, helping developers to understand the bottlenecks and optimize their code for performance.
It usually involves measuring response time, throughput, and scalability metrics. These tests can help with memory leaks, slowdowns due to high traffic, or poorly optimized code.
By running these tests regularly and tracking the results over time, developers can ensure that their system remains performant even as the load increases.
Static code testing helps us find errors in code before they become runtime issues.
It validates our code and ensures it is free of security vulnerabilities and other programming errors.
Besides, it reduces the time spent testing and shortens the feedback cycle.
Several automated static code analysis tools are available to help automate the analysis process.
You can use them to scan your codebase and find flaws quickly and efficiently.
What is Static Application Security Testing - SAST?
Static Application Security Testing (SAST) is a type of software security testing that looks for security vulnerabilities in the source code of an application.
It scans the source code of applications to look for coding problems that could lead to security flaws like buffer overflows, SQL injection, and cross-site scripting attacks. Typically, you perform SAST early in the development process to prevent bugs from being introduced into production systems.
Is it necessary to perform Static code testing in software engineering practices?
Yes, static code testing is necessary for software engineering practices.
It helps to detect bugs in the lines of code before it is compiled and executed.
It also detects various programming errors and issues that could arise in the application during execution. This type of testing helps the software meet its functional and non-functional requirements and provides insight into the quality of the source code.