Static code analysis, also known as static analysis or source code analysis, is the process of examining and evaluating a program's source code before it is run or executed. The primary objective is to find errors, bugs, or vulnerabilities without actually executing the code. This can be particularly useful for finding syntax errors, type mismatches, memory leaks, potential security issues, adherence to coding standards, and other quality-related issues. Here are some key aspects of static code analysis: 1. Automated tools: Static code analysis is often performed with specialized tools that can automatically analyze code for certain types of issues. These tools can scan the codebase and identify potential problems quickly and at scale. 2. Early bug detection: By employing static code analysis in the early stages of development, it's possible to detect and fix issues before they become more costly to resolve later in the development lifecycle. 3. Code quality: Static analysis can help ensure code quality by enforcing coding standards, which might include style guides, architectural standards, or other best practices. 4. Security: Security-focused static analysis tools, sometimes referred to as static application security testing (SAST) tools, are critical for identifying vulnerabilities such as buffer overflows, SQL injection, or cross-site scripting (XSS) issues. Non-static code analysis, on the other hand, includes techniques that require executing the code or parts of it. It's commonly referred to as dynamic analysis. Dynamic code analysis checks the behavior of a program at runtime to identify issues that might not be noticeable in the source code alone. This type of analysis can catch errors that depend on the program's state, user input, or interaction with external systems. Some examples of dynamic analysis techniques are: 1. Unit testing: Writing tests for small pieces of the codebase and running them to ensure they perform as expected. 2. Integration testing: Testing the code with its dependencies to make sure components work together correctly. 3. System testing: Evaluating the complete and integrated software system to ensure it meets the specified requirements. 4. Fuzz testing: Providing random, unexpected, or invalid inputs to the program to see how it behaves, which is useful for discovering security vulnerabilities. Both static and dynamic code analyses are critical components of a robust software development and quality assurance process, helping developers to create more secure, robust, and efficient applications.