Randomness testing is the process of evaluating a sequence of numbers or symbols to determine if it exhibits properties consistent with randomness. This involves assessing the unpredictability and lack of patterns within the data, often using statistical tests to quantify how closely the sequence aligns with a truly random sequence. In the context of algorithmic information theory and Kolmogorov complexity, randomness testing helps distinguish between random sequences and those that can be generated by specific algorithms or patterns.
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