feat: Hamming Code for 32bit values #1431

Original file line number	Diff line number	Diff line change
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	/**
	* github author: chrdek
	* license: GPL-3.0 or later
	*
	* @param {number} b = integer or, binary representation of it
	*
	* The following code generates the "hamming weight" for a binary sequence
	* of 32-bit integer values, producing the relevant integer code for it.
	*
	* Returns the overall of bit count population for values up to 65535, inclusive.
	*
	* This algorithm utilizes minimum amount of byte space reads and can be very easily
	* extended to its 64-bit counterpart.
	*
	**/

	function HammingWeight(b) {
	//preallocate total number of bytes to count the bits population from
	let bytes = new Array(65536);

	//count the bit allocation of the binary sequence by shift in place of the resulting bits
	//can be used with xor as well.
	const bitAlloc = (bin) => {
	let counter = 0;
	while (bin > 0) {
	counter += bin & 1;
	bin >>=1;
	}
	return counter;
	}

	//count all 1-bits from entire bit set
	for (let k=0; k < 65536; k++)
	bytes[k] = bitAlloc(k);

	//perform bit shifting for integer values for bit-populated result
	return bytes[b & 0xFFFF] + bytes[b >> 16];
	}

	export { HammingWeight }

14 changes: 14 additions & 0 deletions Bit-Manipulation/test/HammingWeight.test.js

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	import { HammingWeight } from '../HammingWeight'

	describe.each([
	{ inputVal:Number(117), expectedVal: 5 },
	{ inputVal:parseInt(0x9F9,16), expectedVal: 7 },
	{ inputVal:parseInt(0x889193,16), expectedVal: 10 },
	{ inputVal:10043091, expectedVal: 14},
	{ inputVal:parseInt("1101110",2), expectedVal: 5 },
	{ inputVal:parseInt(1101110,2), expectedVal: 5 }
	])('Resulting code checks from $inputVal', ({inputVal, expectedVal}) => {
	test(`returns ${expectedVal}`, () => {
	expect(HammingWeight(inputVal)).toBe(expectedVal)
	})
	})

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