Intelligent Adaptive Sorting Engine for 32/64-bit Integers & Floating-Point Data
BRESort is an experimental sorting library designed to automatically analyze and optimize sorting strategies based on the underlying structure of your data. It leverages advanced techniques such as:
- Bit entropy analysis to detect patterns at the byte/bit level
- Statistical pattern recognition for data distribution analysis
- Component-wise entropy analysis for floats (sign, exponent, mantissa)
By selecting the most appropriate sorting algorithm for each dataset—like radix sort, quicksort, or hybrid approaches—BRESort achieves significant speedups over standard qsort in many real-world scenarios.
- Up to 12× speedup on structured 32-bit data
- 1.9–2.2× faster on real-world patterns (timestamps, GPS, sensor data)
- 4.6–6.6× faster on 64-bit sequential data
- Consistent 1.1–1.2× gains on floating-point data
- Adaptive intelligence - never significantly slower than optimized quicksort
| Data Type | BRESort | System qsort | Speedup |
|---|---|---|---|
| Database Timestamps | 6.00 ms | 13.00 ms | 2.17× |
| GPS Coordinates | 5.00 ms | 11.00 ms | 2.20× |
| Sensor Readings | 8.00 ms | 15.00 ms | 1.88× |
| 32-bit Sequential | 0.4 ms | 4.8 ms | 12.00× |
- Universal support for 32-bit and 64-bit integers and 32-bit floats
- Automatic algorithm selection based on data characteristics
- Optimized for sequential, random, clustered, and small-range datasets
- Built-in testing and validation framework for correctness and performance
- Stress-tested with edge cases, large datasets, and real-world distributions