Non-compressible Data Stream Generation Using Prime Number Rotation
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Solution Overview
Problem
Conventional methods for generating testing data are inefficient, particularly due to the slowness of hashing and cryptography techniques, and the need for maintaining a master copy of data streams for verification, which can be costly and impractical. Additionally, data compression in testing environments can alter the original data size undesirably.
Innovation Solution
The use of prime numbers to generate non-compressible data streams through initialization parameters and constrained prime numbers, allowing for the creation of unique, reproducible, and high-speed data streams that can be verified without a master copy, and maintaining the original data size by interleaving sequences generated using constrained prime numbers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hashing and cryptography techniques are used to generate testing data, then data integrity and security are improved, but generation speed deteriorates
Solution Approach 1:
The patent segments the data generation process into multiple independent sequences, each generated using simple arithmetic operations with prime numbers. Instead of using a single complex hashing function for the entire dataset, the system divides generation into parallel streams that can be computed efficiently and independently, then combines them to produce the final test data with desired properties.
Solution Approach 2:
The patent changes the fundamental parameter of data generation from cryptographic hashing to arithmetic progression using prime numbers. By modifying the generation algorithm to use simple mathematical operations (addition, multiplication) rather than complex hash functions, the system achieves both high speed and data integrity through the mathematical properties of prime numbers.
2Measurement precision
If a master copy of data stream is maintained for verification, then verification accuracy is improved, but storage cost and complexity deteriorate
Solution Approach 1:
The patent implements self-service verification where the data stream verifies itself through embedded checksums and mathematical relationships. Each generated data stream contains inherent verification mechanisms (such as checksums calculated from the same prime number sequences) that allow verification without external master copies. The system uses the same generation parameters to both create and verify the data, eliminating the need for separate storage.
Solution Approach 2:
The patent introduces mathematical checksums and verification values as intermediaries between the data stream and verification process. Instead of storing and comparing entire master copies, the system uses compact mathematical representations (checksums derived from prime number sequences) that serve as mediators for verification, dramatically reducing storage requirements while maintaining verification accuracy.
3Productivity
If data compression is applied in testing environments, then data transmission efficiency is improved, but original data size and test accuracy deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-calculating and embedding verification checksums and metadata into the data stream before transmission. Instead of compressing the entire dataset and risking loss of verification information, the system prepares the data with built-in verification capabilities ahead of time, ensuring that even after compression and transmission, the original data integrity can be fully verified without accuracy loss.
Data Source
AI summary
Generating non-compressible data streams is disclosed, including: receiving a sequence comprising a plurality of byte values calculated from an initialization parameter and a constrained prime number; determining a data structure index from a plurality of bits within at least one of the plurality of byte values; retrieving a rotation value from a data structure, wherein the rotation value is stored in the data structure at the data structure index; and rotating a portion of the sequence based on a rotation value to form a rotated sequence, wherein the rotated sequence comprises byte values substantially defeating a predictive compression algorithm.