sorting-and-order-statistics

What problem does it solve?

Sorting and order-statistics provide structured methods to extract exact ranks, medians, and top-k elements from data under engineering constraints, avoiding ad-hoc reasoning.

Core Features & Use Cases

• Decision guidance: Choose the right primitive (comparison-based sort, counting/radix, or selection) given key range, stability needs, and payload size.
• Pattern catalog: Highlights when to use quickselect, median-of-medians, heaps, or streaming top-k in production pipelines.
• Use Case: In a data processing task with large datasets, identify the 95th percentile and extract the top-10 records efficiently without fully sorting the dataset.

Quick Start

Translate an ordering requirement into a concrete rank, then apply the appropriate order-statistic primitive to obtain the result.