Welcome to my blog! Since this is my very first post, I thought it would be nice to start with a topic that’s been on my mind a lot during my thesis work: the difference between static and dynamic code analysis.
It sounds academic, but trust me—it shows up in real projects all the time.
Static Analysis: Looking at Code Without Running It
Static analysis basically means checking your code without executing it. The way I usually explain it is by comparing it to reading the blueprints of a building before the first brick is even laid. You’re not testing the house itself—you’re just making sure the plan makes sense.
In practice, this involves things like the Abstract Syntax Tree (AST), which tools use to flag issues in:
- Syntax
- Code structure
- Programming style
It’s a great way to spot whole classes of problems early on, before they sneak into production.
Dynamic Analysis: Seeing Code in Action
Dynamic analysis is the other side of the coin. Here, you actually run the program and watch how it behaves. Using the same house analogy, this would be moving into the finished place, turning on the lights, running the water, and checking if the roof leaks when it rains.
Examples include:
- Unit and integration tests
- Profilers for monitoring performance
- Test coverage tools that show what code hasn’t been exercised
- Spotting runtime exceptions that only pop up when the program is live
Why You Really Need Both
Using just one of these approaches is asking for trouble. Static analysis helps you catch problems early—things like unused variables, suspicious logic, or violations of coding standards. Dynamic analysis, on the other hand, reveals what actually happens when the code runs in the real world.