What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Dynamic type checking verifies at runtime whether a value supports the operation a program is trying to perform. The check happens while the program runs, so a type-related error may appear only when execution reaches the incompatible operation.
What dynamic type checking means
The Python typing documentation defines the timing precisely: “A dynamically typed programming language does not run a type checker before running a program. Instead, it checks the types of values before performing operations on them at runtime.” In other words, a program can start running without a pre-execution type check, but the runtime still checks whether values can be used as requested. See the Python typing documentation on type-system concepts.
For example, an operation such as accessing an attribute or performing arithmetic may be allowed for one value and invalid for another. In a dynamically checked system, the relevant check occurs when the program attempts that operation. Dynamic checking therefore does not mean that values have no types or that every operation is permitted.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →How dynamic checking differs from static checking
| Approach | When checks occur | What that means to a programmer |
|---|---|---|
| Static | Before execution | A checker can identify certain type-rule violations before the program runs. |
| Dynamic | During execution | A type-related failure may surface when execution reaches the incompatible operation. |
| Hybrid or gradual | Some checks before execution, others at runtime | Static analysis and runtime checking can coexist in a language or across parts of a program. |
Static checking can flag some problems earlier, while dynamic checking lets execution proceed until a relevant operation is reached. Neither approach guarantees detection of every defect. Rascal’s documentation describes hybrid checking as performing checks before execution where possible and leaving other checks to runtime; its type-checker documentation explains this division.
Examples: Python and C# show different combinations
Python: runtime checks with optional static analysis
Python is dynamically typed: values have runtime types, and operations are checked as the program performs them. Python also supports annotations that static type-checking tools can use. This gradual approach lets a team check selected code statically without replacing Python’s normal runtime behavior. For instance, a checker may examine a dictionary’s key type while its value type remains subject to runtime checking. The special annotation Any means a type is not known statically to a checker; it does not disable Python’s runtime rules.
C#: the dynamic feature inside a statically typed language
C# is generally statically typed, but its dynamic feature lets particular expressions bypass static type checking. Microsoft describes dynamic as “a static type, but an object of type dynamic bypasses static type checking.” Operations involving such expressions are resolved at runtime. This feature does not make C# as a whole a dynamically typed language. See Microsoft Learn’s explanation of using the C# dynamic type.
JavaScript and Ruby
Oracle’s Java documentation gives JavaScript and Ruby as examples of dynamically typed languages, defining dynamic typing by the fact that type checking occurs at runtime. See Oracle’s documentation on support for non-Java languages.
Free tools Windows power users keep installed
One-click scans. No signup required.
Quick Recap
Best Value
Rank #4
Rank #3
Why check timing matters
- When an issue becomes visible: static checking can identify certain type problems before execution; dynamic checking exposes a problem when the program reaches the operation that violates runtime rules.
- How flexible code can be: runtime decisions can support operations whose validity depends on values encountered while the program runs. Static rules may constrain some patterns, while helping catch certain mismatches earlier.
- How the approaches combine: a language or development workflow can use static analysis for some code and runtime checks for the rest. The distinction is not always an all-or-nothing choice. The University of Cambridge’s lecture materials on static and dynamic type checking discuss the concepts.
What dynamic type checking does not mean
- It does not mean “no types.” Runtime values still have types, and operations must satisfy runtime rules.
- It does not mean every error is caught. The distinction concerns when type-related checks happen, not a guarantee that all bugs will be found.
- It does not always describe an entire language. A language can be mostly statically typed while offering a runtime-resolved feature such as C#’s
dynamic.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
