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feat: Hamming Code for 32bit values #1431

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40 changes: 40 additions & 0 deletions Bit-Manipulation/HammingWeight.js
Original file line number Diff line number Diff line change
@@ -0,0 +1,40 @@
/**
* 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
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
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)
})
})