What are Dynamic-typed and Strongly typed Languages?

Dynamic-typed and Strongly typed languages are two concepts in programming languages related to how variables are handled and how type rules are enforced.

Dynamic–Typed Languages:

In dynamically typed languages, the type of a variable is determined at runtime rather than at compile-time. This means you don’t need to explicitly declare the type of a variable when you write the code. The interpreter infers the type based on the value assigned to the variable.

Characteristics:

• Runtime Type Checking: The type of a variable is checked during execution, allowing variables to change type on the fly.
• Flexibility: Since variables can change types, dynamically typed languages offer more flexibility and can be more concise and easier to write.
• Potential for Runtime Errors: Because type errors are not caught until the code is executed, there’s a higher potential for runtime errors.

Examples:

• Python:

x = 5      # x is an integer

x = “Hello”  # now x is a string

• JavaScript:

let x = 5;      // x is a number

x = “Hello”;    // now x is a string

Strongly Typed Languages:

A strongly typed language enforces strict type rules and does not allow implicit type conversion between different data types. This means that once a variable is assigned a type, it cannot be used in ways that are inconsistent with that type without an explicit conversion.

Characteristics:

• Type Safety: Strongly typed languages prevent operations on incompatible types, reducing bugs and unintended behaviors.
• Explicit Conversions: If you need to convert between types, you must do so explicitly, ensuring that the programmer is aware of and controls the conversion.
• Compile-Time and Runtime Checks: Type enforcement can happen both at compile-time and runtime, depending on the language.

Examples:

• Java (strongly typed, statically typed):

int x = 5;

// x = “Hello”;  // This would cause a compile-time error

• Python (strongly typed, dynamically typed):

x = 5

# x + “Hello”  # This would cause a runtime TypeError

Combining Both Concepts:

Languages can be both dynamic and strongly typed. This means they determine types at runtime but enforce strict type rules once those types are known. Python is a prime example of this combination:

• Python:

x = 10  # x is an integer

y = “20”  # y is a string

# z = x + y  # This raises a TypeError because you can’t add an integer to a string without explicit conversion

Static vs. Dynamic and Strong vs. Weak Typing:

It’s important to distinguish between the dynamic/static and strong/weak typing spectra:

• Static Typing: Types are checked at compile-time (e.g., Java, C++).
• Dynamic Typing: Types are checked at runtime (e.g., Python, JavaScript).
• Strong Typing: Strict enforcement of type rules (e.g., Python, Java).
• Weak Typing: More permissive type rules and implicit conversions (e.g., JavaScript).