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Bloom Filters šŸ†’

Imagine ensuring web safety by identifying malicious links without storing massive data. Traditional methods involve keeping a huge list of bad links, consuming substantial storage and bandwidth. Enter Bloom Filters - a genius method allowing us to significantly reduce storage needs (up to 82% smaller) with a minimal error rate. šŸ‘¾

For instance, instead of a 20MB list for 1,000,000 links, a Bloom Filter achieves this with just 3.59MB, accepting a tiny error chance (0.0001%). Even more impressive, with a 0.1% error tolerance, the size shrinks to 1.8MB. This technique was even utilized by Google Chrome until 2012. āœ”ļø

Bloom Filters offer a balance between efficiency and accuracy. For critical checks, it pairs with a database API for zero false positives. A practical, space-saving solution for modern web browsers! āš”ļø


[ Article ] : https://samwho.dev/bloom-filters

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Algorithm Series šŸ–šŸ“„

Name: Bubble Sort

Type: Comparison sort

Best For: Small datasets

Complexity: O(n²) average and worst-case

How It Works: Repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. The pass through the list is repeated until the list is sorted.

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