Range of values and memory size of all data types

Selecting the appropriate data type is essential for optimizing both the performance and memory usage of a C++ program. Understanding the range and size of each data type allows developers to make informed decisions based on the specific requirements of their application, ensuring efficient and effective code.

Data TypeMemory SizeMinimum ValueMaximum Value
bool1 bytefalse (0)true (1)
char1 byte-128127
unsigned char1 byte0255
short2 bytes-32,76832,767
unsigned short2 bytes065,535
int4 bytes-2,147,483,6482,147,483,647
unsigned int4 bytes04,294,967,295
long4 or 8 bytes-2,147,483,648 to -9,223,372,036,854,775,8082,147,483,647 to 9,223,372,036,854,775,807
unsigned long4 or 8 bytes04,294,967,295 to 18,446,744,073,709,551,615
long long8 bytes-9,223,372,036,854,775,8089,223,372,036,854,775,807
unsigned long long8 bytes018,446,744,073,709,551,615
float4 bytes~1.2E-38~3.4E+38
double8 bytes~2.3E-308~1.7E+308
long double8, 12, or 16 bytes~3.4E-4932~1.1E+4932

Considerations for Choosing Data Types

  1. Memory Efficiency
    • Small Data Types: Use smaller data types (char, short) when memory conservation is critical, especially in large arrays or embedded systems.
    • Floating-Point Numbers: Use float for single-precision calculations when memory usage is more important than precision. Use double for double-precision calculations where accuracy is more critical.
  2. Performance
    • Integer Operations: Generally, integer operations are faster than floating-point operations. Choose int or unsigned int for loop counters and indices.
    • Floating-Point Operations: While slower, float and double are necessary for calculations requiring fractional values.
  3. Range Requirements
    • Signed vs. Unsigned: Use unsigned types (unsigned int, unsigned long) when negative values are not needed, to extend the positive range.
    • Extended Range: Use long long or unsigned long long for very large integers.
  4. Platform-Specific Behavior
    • Cross-Platform Development: Be aware of differences in long and long double sizes across platforms. Always verify with the target platform’s specifications.
  5. Precision and Accuracy
    • Precision Needs: For scientific computations requiring high precision, prefer double or long double.
    • Accumulated Error: Be cautious of accumulated rounding errors in floating-point arithmetic, especially in iterative calculations.

Additional Considerations

  • Type Conversions: Be cautious with implicit type conversions between signed and unsigned types to avoid unexpected behavior or overflow errors.
  • Type Safety: Use static_cast for explicit type conversions to improve code readability and safety.
  • Standard Library Types: Consider using standard library types like std::int32_t or std::uint64_t from <cstdint> for more explicit type definitions and better cross-platform consistency.