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Pseudorandom Number Generators vs True Random Number Generators

Developers should learn PRNGs when building applications that require random-like behavior without the overhead or unpredictability of true randomness, such as in game development for procedural content generation, simulations for testing algorithms, or cryptographic systems for generating keys and nonces meets developers should learn and use trngs when building systems that require high levels of security and unpredictability, such as cryptographic key generation, secure authentication tokens, or lottery systems. Here's our take.

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Pseudorandom Number Generators

Developers should learn PRNGs when building applications that require random-like behavior without the overhead or unpredictability of true randomness, such as in game development for procedural content generation, simulations for testing algorithms, or cryptographic systems for generating keys and nonces

Pseudorandom Number Generators

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Developers should learn PRNGs when building applications that require random-like behavior without the overhead or unpredictability of true randomness, such as in game development for procedural content generation, simulations for testing algorithms, or cryptographic systems for generating keys and nonces

Pros

  • +They are crucial in scenarios where reproducibility is needed, like in scientific computing or unit testing, and offer high performance and scalability compared to hardware-based random sources
  • +Related to: cryptography, algorithm-design

Cons

  • -Specific tradeoffs depend on your use case

True Random Number Generators

Developers should learn and use TRNGs when building systems that require high levels of security and unpredictability, such as cryptographic key generation, secure authentication tokens, or lottery systems

Pros

  • +They are critical in applications where pseudorandomness could be exploited, such as in encryption algorithms or online casinos, to ensure fairness and prevent attacks
  • +Related to: cryptography, pseudorandom-number-generators

Cons

  • -Specific tradeoffs depend on your use case

The Verdict

Use Pseudorandom Number Generators if: You want they are crucial in scenarios where reproducibility is needed, like in scientific computing or unit testing, and offer high performance and scalability compared to hardware-based random sources and can live with specific tradeoffs depend on your use case.

Use True Random Number Generators if: You prioritize they are critical in applications where pseudorandomness could be exploited, such as in encryption algorithms or online casinos, to ensure fairness and prevent attacks over what Pseudorandom Number Generators offers.

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The Bottom Line
Pseudorandom Number Generators wins

Developers should learn PRNGs when building applications that require random-like behavior without the overhead or unpredictability of true randomness, such as in game development for procedural content generation, simulations for testing algorithms, or cryptographic systems for generating keys and nonces

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