RNG Generator

This tool provides deterministic or non-deterministic random numbers within a user-specified range. It targets developers, data scientists, QA engineers, and students who need quick, repeatable randomness for tests, simulations, and demonstrations. Users supply a minimum and maximum bound, a count of numbers to generate, and an optional seed to control reproducibility. The tool returns an array of numbers suitable for unit tests, Monte Carlo experiments, or teaching exercises without relying on external services or cryptographic methods.
Conceptually, the engine implements a uniform distribution by converting a pseudo-random value in the interval [0,1) into the desired range [min, max] and applying inclusive bounds as configured. A provided seed yields a deterministic sequence across invocations, while omitting the seed produces fresh values each run. Outputs can be integers or floating-point numbers, and the count parameter controls the length of the result array.
In practice the tool offers a lean, transparent approach to randomness. It does not rely on external entropy sources unless a user-supplied seed is present, ensuring reproducibility and portability across languages and environments. Advanced features include multiple output formats, the option to generate grouped results, and clean JSON export for integration into tests or data pipelines. The core differentiators are predictable seeding, explicit range mapping, and a compact, dependency-free core suitable for embedded testing tasks.
Common use cases include unit test data generation, probabilistic simulations, classroom demonstrations of randomness, and quick benchmarking where repeatability matters; it also serves as a teaching aid for probability topics and statistical method prototyping.