C++
- Getting started with C++
- Awesome Book
- Awesome Community
- Awesome Course
- Awesome Tutorial
- Awesome YouTube
- Alignment
- Argument Dependent Name Lookup
- Arithmitic Metaprogramming
- Arrays
- Atomic Types
- Attributes
- auto
- Basic input/output in c++
- Basic Type Keywords
- Bit fields
- Bit Manipulation
- Bit Operators
- Build Systems
- C incompatibilities
- C++ Containers
- C++ Debugging and Debug-prevention Tools & Techniques
- C++ function "call by value" vs. "call by reference"
- C++ Streams
- C++11 Memory Model
- Callable Objects
- Classes/Structures
- Client server examples
- Common compile/linker errors (GCC)
- Compiling and Building
- Concurrency With OpenMP
- Const Correctness
- const keyword
- Constant class member functions
- constexpr
- Copy Elision
- Copying vs Assignment
- Curiously Recurring Template Pattern (CRTP)
- Data Structures in C++
-
Date and time using
header - decltype
- Design pattern implementation in C++
- Digit separators
- Enumeration
- Exceptions
- Explicit type conversions
- Expression templates
- File I/O
- Floating Point Arithmetic
- Flow Control
- Fold Expressions
- Friend keyword
- Function Overloading
- Function Template Overloading
- Futures and Promises
- Header Files
- Implementation-defined behavior
- Inline functions
- Inline variables
- Internationalization in C++
- Iteration
- Iterators
- Keywords
- Lambdas
- Layout of object types
- Linkage specifications
- Literals
- Loops
- Memory management
- Metaprogramming
- More undefined behaviors in C++
- Move Semantics
- mutable keyword
- Mutexes
- Namespaces
- Non-Static Member Functions
- One Definition Rule (ODR)
- Operator Overloading
- operator precedence
- Optimization
- Optimization in C++
- Overload resolution
- Parameter packs
- Perfect Forwarding
- Pimpl Idiom
- Pointers
- Pointers to members
- Polymorphism
- Preprocessor
- Profiling
- RAII: Resource Acquisition Is Initialization
- Random number generation
- True random value generator
- Generating a pseudo-random number
- Using the generator for multiple distributions
- Recursion in C++
- Recursive Mutex
- Refactoring Techniques
- References
- Regular expressions
- Resource Management
- Return Type Covariance
- Returning several values from a function
- RTTI: Run-Time Type Information
- Scopes
- Semaphore
- SFINAE (Substitution Failure Is Not An Error)
- Side by Side Comparisons of classic C++ examples solved via C++ vs C++11 vs C++14 vs C++17
- Singleton Design Pattern
- Smart Pointers
- Sorting
- Special Member Functions
- Standard Library Algorithms
- static_assert
- std::any
- std::array
- std::atomics
- std::forward_list
- std::function: To wrap any element that is callable
- std::integer_sequence
- std::iomanip
- std::map
- std::optional
- std::pair
- std::set and std::multiset
- std::string
- std::variant
- std::vector
- Storage class specifiers
- Stream manipulators
- Templates
- The ISO C++ Standard
- The Rule of Three, Five, And Zero
- The This Pointer
- Thread synchronization structures
- Threading
- Trailing return type
- type deduction
- Type Erasure
- Type Inference
- Type Keywords
- Type Traits
- Typedef and type aliases
- Undefined Behavior
- Unions
- Unit Testing in C++
- Unnamed types
- Unspecified behavior
- User-Defined Literals
- Using declaration
- Using std::unordered_map
- Value and Reference Semantics
- Value Categories
- Variable Declaration Keywords
- Virtual Member Functions
C++ Random number generation
Remarks
Random number generation in C++ is provided by the <random> header. This header defines random devices, pseudo-random generators and distributions.
Random devices return random numbers provided by operating system. They should either be used for initialization of pseudo-random generators or directly for cryptographic purposes.
Pseudo-random generators return integer pseudo-random numbers based on their initial seed. The pseudo-random number range typically spans all values of an unsigned type. All pseudo-random generators in the standard library will return the same numbers for the same initial seed for all platforms.
Distributions consume random numbers from pseudo-random generators or random devices and produce random numbers with necessary distribution. Distributions are not platform-independent and can produce different numbers for the same generators with the same initial seeds on different platforms.
Random number generation Related Examples
- True random value generator
- Generating a pseudo-random number
- Using the generator for multiple distributions
