Data Type | Notion

Certainly! Understanding the limits and properties of different data types is crucial for solving problems efficiently in C++. Here's a table with the limits for common data types, along with some explicit properties:

Limits of Common Data Types

Data Type	Size (in bytes)	Minimum Value	Maximum Value	Notes
`char`	1	-128 (signed) or 0 (unsigned)	127 (signed) or 255 (unsigned)	Used for characters and small integers.
`short`	2	-32,768	32,767	Shorter range compared to `int`.
`int`	4	-2,147,483,648	2,147,483,647	Commonly used for integer operations.
`long`	4 (32-bit) or 8 (64-bit)	-2,147,483,648 (32-bit) or -9,223,372,036,854,775,808 (64-bit)	2,147,483,647 (32-bit) or 9,223,372,036,854,775,807 (64-bit)	Can be 32-bit or 64-bit depending on the system.
`long long`	8	-9,223,372,036,854,775,808	9,223,372,036,854,775,807	Guarantees at least 64-bit representation.
`float`	4	Approx. -3.4 × 10^38	Approx. 3.4 × 10^38	Precision up to 7 decimal digits.
`double`	8	Approx. -1.7 × 10^308	Approx. 1.7 × 10^308	Precision up to 15-16 decimal digits.
`long double`	8, 12, or 16	Approx. -1.1 × 10^4932	Approx. 1.1 × 10^4932	Precision can exceed `double`, size varies by system.

Explicit Properties

Integer Types (int, long, long long):
- Overflow: When an operation results in a value outside the range of the data type, it causes overflow or underflow, leading to unexpected results.
- Arithmetic Operations: Operations on integers follow integer arithmetic rules; be cautious with division by zero and truncation.
- Signed vs Unsigned: Signed types can represent both negative and positive values, while unsigned types only represent positive values.
Floating-Point Types (float, double, long double):
- Precision: Floating-point types are approximate representations and can suffer from precision errors. float has less precision compared to double, and long double provides more precision but varies by system.
- Overflow and Underflow: Similar to integers, floating-point numbers can also overflow or underflow. However, they often do so with a gradual loss of precision rather than abrupt wrap-around.
- Representation: Floating-point numbers are represented in scientific notation, which can lead to rounding errors during arithmetic operations.
Type Conversion:
- Implicit Conversion: C++ performs implicit type conversion when mixing different types in operations. For example, int and float in an expression will result in a float.
- Explicit Conversion (Casting): Use static_cast, dynamic_cast, const_cast, or reinterpret_cast for explicit type conversions. Be cautious of precision loss or invalid conversions.

Examples

#include <iostream>
#include <limits>

int main() {
    std::cout << "int max: " << std::numeric_limits<int>::max() << std::endl;
    std::cout << "long long min: " << std::numeric_limits<long long>::min() << std::endl;
    std::cout << "float max: " << std::numeric_limits<float>::max() << std::endl;
    std::cout << "double precision: " << std::numeric_limits<double>::digits10 << std::endl;
    return 0;
}

This code uses <limits> to display the maximum and minimum values of various data types, as well as the precision of double.

Feel free to add these details to your Notion notes for reference. If you need further elaboration on any specific data type or property, just let me know!

Order

Double