Specify a condition-based binary code in constant time - java

Problem formulation: Given two integer t and l, specify a binary code of length l such that we have bits of value 1 every (t-1) bits in constant time.
For example, given t=3 and l=10, the result is 1001001001.
The solution I can think of is to conducting some shiftings of a binary code of value 1:
A1=1
A2=A1>>3
A3=A1>>(3x2)
result=A1||A2||A3
However, this solution is not efficient.
What I want is to solve this problem in constant time.

May be you need something like this :
public class SomeClass {
public static void main(String args[]) {
int l = 15;
for(int t = 1; t < 10; ++t) {
System.out.println(t + " " + l + " => " + toBinString(solve(t, l), l));
}
}
public static String toBinString(int value, int length) {
String s = "";
for(int i = 0; i < length; ++i)
s += (char)('0' + (value >> i & 1));
return s;
}
public static int solve(int t, int l) {
return ((1 << (l + t - 1)) - 1) / ((1 << t) - 1);
}
}
Output :
1 15 => 111111111111111
2 15 => 101010101010101
3 15 => 001001001001001
4 15 => 001000100010001
5 15 => 000010000100001
6 15 => 001000001000001
7 15 => 100000010000001
8 15 => 000000100000001
9 15 => 000001000000001

Related

What happens when you shift an int left

I'm trying to understand part of this code that was created here to create a my_hashset: https://leetcode.com/problems/design-hashset/discuss/548792/Java-solution-faster-than-99
class HashCode_from_leet {
int[] bitArr;
private static final int MAX = 100000;
private static final int INT_SIZE = Integer.SIZE;
public HashCode_from_leet() {
bitArr = new int[MAX / INT_SIZE + 1];
}
public void add(int key) { //pass in 5
int ind = key / INT_SIZE;
int bit = key % INT_SIZE;
int bitMask = 1 << bit; //QUESTION: why does bitMask = 32?
bitArr[ind] |= bitMask; // QUESTION: what does '|=' mean?
}
// NOTE I REMOVED SOME METHODS
public boolean contains(int key) {
int ind = key / INT_SIZE;
int bit = key % INT_SIZE;
int bitMask = 1 << bit;
return (bitArr[ind] & bitMask) != 0;
}
public static void main(String[] args) {
HashCode_from_leet hfl = new HashCode_from_leet();
hfl.add(5);
System.out.println(hfl.contains(5));
}
}
When I pass in 5 into the add(int key) method
bitMask = 32
I'm not sure why -- I understand << means shift left, so we take 5 and shift it left, but would think that equals 5*10^2?
When you shift left an integer by X eg: Z =(Y << X) it will acutally do this operation
: Z = (Y * (2^X))
When you shift right an integer by X eg: Z =(Y >> X) it will acutally do this operation
: Z = (Y / (2^X))
what happens when you shift an int left
As the name suggests, left-shifting a number by n places, multiplies it by 2^n. The following code will help you understand it better.
public class Main {
public static void main(String[] args) {
int x = 5;
System.out.println("In decimal: " + x + ", In Binary: "
+ "0000000000000000".substring(Integer.toBinaryString(x).length()) + Integer.toBinaryString(x));
int y = x << 1;
System.out.println("In decimal: " + y + ", In Binary: "
+ "0000000000000000".substring(Integer.toBinaryString(y).length()) + Integer.toBinaryString(y));
int z = x << 2;
System.out.println("In decimal: " + z + ", In Binary: "
+ "0000000000000000".substring(Integer.toBinaryString(z).length()) + Integer.toBinaryString(z));
}
}
Output:
In decimal: 5, In Binary: 0000000000000101
In decimal: 10, In Binary: 0000000000001010
In decimal: 20, In Binary: 0000000000010100
Notice line int bit = key % INT_SIZE; // which is 5 % 32 according to your code
So now bit = 5 // because 5 % 32 = 5
Now int bitMask = 1 << bit; // you're saying shit 1 to five bits to left
in 32 bits 1 = 000000000000000000000000000000000001
After shifting 5 bits to left it becomes:
000000000000000000000000000000000100000 = 32 //in binary that is why bitmask continas 32
Now let's talk about |= operator
| is a bitwise OR operator you are just using as compound assignment
bitArr[ind] |= bitMask is similar to bitArr[ind] = bitArr[ind] | bitmask
For example say bitArr[ind] equals 5 and bitmask equals 3
now bitArr[ind] | bitmask means 5 | 3
It will do bitwise OR with binary representation
means 101 | 011 which becomes 111 which is 7

Algorithm will not encrypt/decrypt properly

I tested the below code with all ASCII values from 64 - 90 inclusive (All uppercase letters) and adjusted accordingly so instead of:
for(int i = 0 ; i < c.length(); i++){
info[i] = ((int)c.charAt(i) - 32);
}
I would replace the 32 with 64 (so the ASCII value of A would save in the array as 0). Furthermore, in my encryption and decryption functions I would replace 95 with 26 (26 letters).
However, if I apply this to all values between 32-126 inclusive (95 characters) and adjust the values accordingly, the values become incorrect and I don't know why. Here is my whole main function below (note that the formula used in encryption and decryption is just an example one I used and I plan on changing the values later on):
public static void main(String[] args) {
String c = "sd344rf"; // could be any set of characters within the range
int[] e = new int[c.length()]; // encrypted set
int[] d = new int[c.length()]; // decrypted set
int[] info = new int[c.length()];
for(int i = 0 ; i < c.length(); i++){
info[i] = ((int)c.charAt(i) - 32);
}
for(int i = 0; i < c.length(); i++){
e[i] = encryption(info[i]);
}
for(int i = 0; i < c.length(); i++){
d[i] = decryption(e[i]);
}
display(info);
System.out.println();
display(e);
System.out.println();
display(d);
}
public static int encryption(int x){
return mod(3*x + 9,95);
}
public static int decryption(int x){
return mod(9*x - 3,95);
}
public static void display(int[] arr){
for(int i = 0; i < arr.length; i++){
System.out.print(arr[i] + " ");
}
}
}
Obviously you are trying to implement an affine cipher. For an affine cipher the encryption is
y = mod(n * x + s, m)
and the decryption
x = mod(ni * (y - s), m)
with
x: Value of the character to encrypt
y: Value of the encrypted character
m: Number of characters in the underlying alphabet
n, s: Key of the encryption
n and s must be chosen so that they are between 0 and m - 1, inclusive. In addition, n has to be chosen so that n and m are coprime. ni is the modular multiplicative inverse of n modulo m and is determined by n*ni mod m = 1.
This is in more detail explained at https://en.wikipedia.org/wiki/Affine_cipher.
If the values u, v associated with the characters don't start at 0 the values have to be shifted by an offset equal to the value of the first character (provided that there are no gaps) and the formulas become
x = u - offset
y = v - offset
v = mod(n * (u - offset) + s, m) + offset
u = mod(ni * ((v - offset) - s), m) + offset
Thus, you've to replace in the main-method
info[i] = ((int)c.charAt(i) - 32);
with
info[i] = (int)c.charAt(i);
The encryption-method becomes:
public static int encryption(int u) {
return mod(n * (u - offset) + s, m) + offset;
}
and the decryption-method
public static int decryption(int v) {
return mod(ni * ((v - offset) - s), m) + offset;
}
with the fields
private static int m = <Number of the characters in the alphabet>;
private static int n = <Key (factor)>; // n between 0 and m-1 and moreover, n and m have te be coprime
private static int s = <Key (summand)>; // s between 0 and m-1
private static int offset = <Value of the first character of the alphabet>;
private static int ni = <Modular multiplicative inverse of n modulo m>;
Moreover, for the mod-operation the following method is used (see Encryption/decryption program not working properly):
private static int mod(int a, int b) {
return ((a % b) + b) % b;
}
Example 1: Uppercase letters A - Z:
private static int m = 'Z' - 'A' + 1; // 26
private static int n = 3; // Choose e.g. n = 3: n = 3 < 26 - 1 = 25 and moreover, 3 and 26 are coprime
private static int s = 9; // Choose e.g. s = 9: s = 9 < 26 - 1 = 25
private static int offset = 'A'; // 65
private static int ni = 9; // 3*9 mod 26 = 1
Test:
String c = "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
Output (with characters instead of their values):
Plain text: ABCDEFGHIJKLMNOPQRSTUVWXYZ
Encrypted text: JMPSVYBEHKNQTWZCFILORUXADG
Decrypted text: ABCDEFGHIJKLMNOPQRSTUVWXYZ
Example 2: All characters between 32 (Space) and 126 (~), inclusive:
private static int m = '~' - ' ' + 1; // 95
private static int n = 3; // Choose e.g. n = 3: n = 3 < 95 - 1 = 94 and moreover, 3 and 95 are coprime
private static int s = 9; // Choose e.g. s = 9: s = 9 < 95 - 1 = 94
private static int offset = ' '; // 32
private static int ni = 32; // 3*32 mod 95 = 1
Test:
String c = " !\"#$%&'()*+,-./0123456789:;<=>?#ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~";
Output (with characters instead of their values):
Plain text: !"#$%&'()*+,-./0123456789:;<=>?#ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~
Encrypted text: ),/258;>ADGJMPSVY\_behknqtwz}!$'*-0369<?BEHKNQTWZ]`cfilorux{~"%(+.147:=#CFILORUX[^adgjmpsvy| #&
Decrypted text: !"#$%&'()*+,-./0123456789:;<=>?#ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~

Converting to base 10 in java?

I have a homework assignment where I have to covert any base to base 10. I have some given numbers, which are the "basen". I have to convert those bases to base 10. The only part that I am stuck in is this part of the code:
answer = ; // Not sure what I have to put in here
I have seen some other posts about converting to base ten, but I am just not sure how to how to incorporate them into my code.
public class BaseN {
public static final int BASEN_ERRNO = -1;
public static int digit = 0;
public static void main(String[] argv) {
basen(512, 6);
basen(314, 8);
basen(49, 5);
basen(10101, 2);
}
public static void basen(int n, int b) {
int ans = basen(n, b, 1, 0);
if (ans == BASEN_ERRNO)
System.out.println(n + " is not a valid base-" + b + " number");
else
System.out.println(n + " base-" + b + " = " + ans + " base-10");
}
public static int basen(int number, int base, int placevalue, int answer) {
if (number == 0) return answer;
digit = number % 10;
if (digit >= base) return BASEN_ERRNO;
answer = 1;// not sure what to put here
number = 0;
placevalue = 0;
return basen(number, base, placevalue, answer);
}
}
You could look at a k length number of base n like this:
x(0)*n^(k-1) + x(1)*n^(k-2) + ... + x(k-1)*n^1 + x(k)*n^0
Where x(0), x(1), ..., x(k) is the digit at position k from the left.
So, if you are trying to convert, say, 101 base 2 to base 10 you would do the following :
1 * 2^2 + 0 * 2^1 + 1 * 2^0 = 4 + 0 + 1 = 5 base 10
say you want to convert the number 352 from base 6:
3 * 6^2 + 5 * 6^1 + 2 * 6^0 = 108 + 30 + 2 = 145 base 10
What you're looking for code wise is something like this :
int[] digits = {3, 5, 2};
int base = 6;
int answer = 0;
for(int i = digits.length - 1; i >= 0; i--)
{
answer += digits[i] * Math.pow(base,digits.length-i-1);
}
return answer;
which will return 145.
Hopefully even though my implementation is iterative you should be able to apply it to your recursive implementation as well.
You can implement the following algorithm. Lets say you are given String number which represents the number you want to convert to decimal form and int base which represents the base of given number. You can implement function int convertToNumber(char c); which accepts one character representing one digit from your number and will map characters to numbers like this:
0 -> 0,
1 -> 1,
... ,
A-> 10,
B -> 11,
... ,
F -> 15,
...
Then you just iterate through your given string and multiply this functions output with base to the power of iteration. For example, convert number A32(hexadecimal):
A32 = convertToNumber(A) * b ^ 2 + convertToNumber(3) * b ^ 1 + convertToNumber(2) * b ^ 0 = 10 * 16 ^ 2 + 3 * 16 ^ 1 + 2 * 16 ^ 0 = 10 * 16 * 16 + 3 * 16 + 2 = 2610 (decimal).
public class BaseConvert {
public static int convertDigitToNumber(char c) throws Exception {
if(c >= '0' && c <= '9') return c - '0';
if(c >= 'A' && c <= 'Z') return c - 55;
if(c >= 'a' && c <= 'z') return c - 97;
throw new Exception("Invalid digit!");
}
public static int convertToBase(String number, int base) throws Exception {
int result = 0;
for(int i = 0; i < number.length(); i++){
result += convertDigitToNumber(number.charAt(i)) * (int)Math.pow(base, number.length() - i - 1);
}
return result;
}
public static void main(String[] args) {
try{
System.out.println(convertToBase("732", 8));
System.out.println(convertToBase("A32", 16));
System.out.println(convertToBase("1010", 2));
}catch (Exception e) {
System.out.print(e);
}
}
}

nth Binary palindrome with efficient time complexity

Given an integer N, i am trying to find the nth binary palindrome.I have written the following code but it is not efficient.is there a more efficient way in terms of time complexity.
I was trying it out as a problem online and i was supposed to output in 1 sec or less but for every input it takes 2 seconds.
public static Boolean Palind(String n){
String reverse = "";
int length = n.length();
for(int i = length - 1; i >=0;i--){
reverse = reverse + n.charAt(i);
}
if(n.equals(reverse)){
return true;
}
else{
return false;
}
}
public static int Magical(int n){
ArrayList<Integer> res = new ArrayList<Integer>();
for(int i = 1; i < Math.pow(2, n);i++){
if(Palind(Integer.toBinaryString(i))){
res.add(i);
}
}
return res.get(n-1);
}
The relevant OEIS entry (A006995) has a lot of nice tips if you read through it. For example, a(2^n-1)=2^(2n-2)-1 lets you skip right to the (2n - 1)th palindrome really quickly.
It also gives several implementations. For example, the Smalltalk implementation works like this (note that the input value, n, starts with 1 for the first palindrome, 0):
public static final int nthBooleanPalindrome(int n) {
if (n == 1) return 0;
if (n == 2) return 1;
int m = 31 - Integer.numberOfLeadingZeros(n);
int c = 1 << (m - 1);
int b;
if (n >= 3*c) {
int a = n - 3*c;
int d = 2*c*c;
b = d + 1;
int k2 = 1;
for (int i = 1; i < m; i++) {
k2 <<= 1;
b += a*k2/c%2*(k2 + d/k2);
}
}
else {
int a = n - 2*c;
int d = c*c;
b = d + 1 + (n%2*c);
int k2 = 1;
for (int i = 1; i < m - 1; i++) {
k2 <<= 1;
b += a*k2/c%2*(k2 + d/k2);
}
}
return b;
}
Try something like this maybe?
public static void main(String[] args) {
for (int i = 1; i < 65535; i++) {
System.out.println(
i + ": " + getBinaryPalindrom(i) + " = " + Integer.toBinaryString(getBinaryPalindrom(i)));
}
}
public static int getBinaryPalindrom(int N) {
if (N < 4) {
switch (N) {
case 1:
return 0;
case 2:
return 1;
case 3:
return 3;
}
throw new IndexOutOfBoundsException("You need to supply N >= 1");
}
// second highest to keep the right length (highest is always 1)
final int bitAfterHighest = (N >>> (Integer.SIZE - Integer.numberOfLeadingZeros(N) - 2)) & 1;
// now remove the second highest bit to get the left half of our palindrom
final int leftHalf = (((N >>> (Integer.SIZE - Integer.numberOfLeadingZeros(N) - 1)) & 1) << (Integer.SIZE -
Integer.numberOfLeadingZeros(N) - 2)) | ((N << (Integer.numberOfLeadingZeros(N) + 2)) >>> (Integer.numberOfLeadingZeros(N) + 2));
// right half is just the left reversed
final int rightHalf = Integer.reverse(leftHalf);
if (Integer.numberOfLeadingZeros(leftHalf) < Integer.SIZE / 2) {
throw new IndexOutOfBoundsException("To big to fit N=" + N + " into an int");
}
if (bitAfterHighest == 0) {
// First uneven-length palindromes
return (leftHalf << (Integer.SIZE - Integer.numberOfLeadingZeros(leftHalf)) - 1) | (rightHalf
>>> Integer.numberOfTrailingZeros(rightHalf));
} else {
// Then even-length palindromes
return (leftHalf << (Integer.SIZE - Integer.numberOfLeadingZeros(leftHalf))) | (rightHalf
>>> Integer.numberOfTrailingZeros(rightHalf));
}
}
The idea is that each number will become a palindrome once it reverse is added. To have the halves correctly aligned the halves just need to be shifted in place.
The problem why this has gotten a bit complex is that all uneven-length palindromes of a given leftHalf length come before all even-length palindromes of a given leftHalf length. Feel free to provide a better solution.
As int has 32 bit in Java there is a limit on N.
int-Version on ideone.com
And a BigInteger-version to support big values. It is not as fast as the int-version as the byte[]-arrays which store the value of the BigInteger create some overhead.
public static void main(String[] args) {
for (BigInteger i = BigInteger.valueOf(12345678); i.compareTo(BigInteger.valueOf(12345778)) < 0; i = i
.add(BigInteger
.ONE)) {
final BigInteger curr = getBinaryPalindrom(i);
System.out.println(i + ": " + curr + " = " + curr.toString(2));
}
}
public static BigInteger getBinaryPalindrom(BigInteger n) {
if (n.compareTo(BigInteger.ZERO) <= 0) {
throw new IndexOutOfBoundsException("You need to supply N >= 1");
} else if (n.equals(BigInteger.valueOf(1))) {
return BigInteger.valueOf(0);
} else if (n.equals(BigInteger.valueOf(2))) {
return BigInteger.valueOf(1);
} else if (n.equals(BigInteger.valueOf(3))) {
return BigInteger.valueOf(3);
}
final int bitLength = n.bitLength() - 1;
// second highest to keep the right length (highest is always 1)
final boolean bitAfterHighest = n.testBit(bitLength - 1);
// now remove the second highest bit to get the left half of our palindrom
final BigInteger leftHalf = n.clearBit(bitLength).setBit(bitLength - 1);
// right half is just the left reversed
final BigInteger rightHalf;
{
byte[] inArray = leftHalf.toByteArray();
byte[] outArray = new byte[inArray.length];
final int shiftOffset = Integer.SIZE - Byte.SIZE;
for (int i = 0; i < inArray.length; i++) {
outArray[inArray.length - 1 - i] = (byte) (Integer.reverse(inArray[i]) >>> shiftOffset);
}
rightHalf = new BigInteger(1, outArray).shiftRight(outArray.length * Byte.SIZE - bitLength);
}
if (!bitAfterHighest) {
// First uneven-length palindromes
return leftHalf.shiftLeft(bitLength - 1).or(rightHalf);
} else {
// Then even-length palindromes
return leftHalf.shiftLeft(bitLength).or(rightHalf);
}
}
I have the same idea with #Kiran Kumar: you should not count number one by one to find if it is a binary palindrome which is too slow, but rather find the internal pattern that number has.
List the number in binary string one by one, you can find the pattern:
0
1
11
101
1001
1111
...
1......1
And the following is some math problem:
We have 2^round_up((L-2)/2) palindrome of number with length L in binary format.
Sum up every shorter length number, we get following len to sum mapping:
for (int i = 1; i < mapping.length; i++) {
mapping[i] = (long) (mapping[i - 1] + Math.pow(2, Math.ceil((i - 1) * 1.0 / 2)));
}
If we find N range in [count(L), count(L+1)), we can concat it with remaining number:
public static long magical(long n) {
if (n == 0 || n == 1) {
return n;
}
long N = n - 2;
return Long.parseLong(concat(N), 2);
}
private static String concat(long N) {
int midLen = Arrays.binarySearch(indexRange, N);
if (midLen < 0) {
midLen = -midLen - 1;
}
long remaining = N - indexRange[midLen];
String mid = mirror(remaining, midLen);
return '1' + mid + '1';
}
private static String mirror(long n, int midLen) {
int halfLen = (int) Math.ceil(midLen * 1.0 / 2);
// produce fixed length binary string
final String half = Long.toBinaryString(n | (1 << halfLen)).substring(1);
if (midLen % 2 == 0) {
return half + new StringBuilder(half).reverse().toString();
} else {
return half + new StringBuilder(half).reverse().toString().substring(1);
}
}
Full code with test for produce large possible long can be found in my git repo.
Idea to optimize,
Let's look at the palindrome sequence 0, 1, 11, 101, 111, 1001 etc...
All numbers must begin and end with 1, So the middle bits only changes and midle substring should be palindrome for full string to become palindrome,
So let's take a 2 digit binary number - one palindrome is possible.
The binary of the decimal 3 is a palindrome. 11
For a 3 digit binary number 2 palindromes are possible, 2*(no of 1 digit palindrome)
The binary of the decimal 5 is a palindrome. 101
The binary of the decimal 7 is a palindrome. 111
For 5 digit binary number 4 palindromes are possible 2*(no of 3 digit palindrome)
10001,10101, 11011, 11111
and so on,
So it will be 2 + 20 + 21 + 22 +...... +2i-N ,
we solve for i and find out the palindrome number.
So by analysing this sequence we get an equation like 2(i/2)+1 -1 = N
where N is the No of palindrome,
and i is the number of bits in the nth palindrome string,
using this we can find the length of the String, from this we can find the string early.
This might be complex, but helps in solving higher values of N quickly....

How can I perform multiplication without the '*' operator?

I was just going through some basic stuff as I am learning C. I came upon a question to multiply a number by 7 without using the * operator. Basically it's like this
(x << 3) - x;
Now I know about basic bit manipulation operations, but I can't get how do you multiply a number by any other odd number without using the * operator? Is there a general algorithm for this?
Think about how you multiply in decimal using pencil and paper:
12
x 26
----
72
24
----
312
What does multiplication look like in binary?
0111
x 0101
-------
0111
0000
0111
-------
100011
Notice anything? Unlike multiplication in decimal, where you need to memorize the "times table," when multiplying in binary, you are always multiplying one of the terms by either 0 or 1 before writing it down in the list addends. There's no times table needed. If the digit of the second term is 1, you add in the first term. If it's 0, you don't. Also note how the addends are progressively shifted over to the left.
If you're unsure of this, do a few binary multiplications on paper. When you're done, convert the result back to decimal and see if it's correct. After you've done a few, I think you'll get the idea how binary multiplication can be implemented using shifts and adds.
Everyone is overlooking the obvious. No multiplication is involved:
10^(log10(A) + log10(B))
The question says:
multiply a number by 7 without using * operator
This doesn't use *:
number / (1 / 7)
Edit:
This compiles and works fine in C:
int number,result;
number = 8;
result = number / (1. / 7);
printf("result is %d\n",result);
An integer left shift is multiplying by 2, provided it doesn't overflow. Just add or subtract as appropriate once you get close.
int multiply(int multiplicand, int factor)
{
if (factor == 0) return 0;
int product = multiplicand;
for (int ii = 1; ii < abs(factor); ++ii) {
product += multiplicand;
}
return factor >= 0 ? product : -product;
}
You wanted multiplication without *, you got it, pal!
It's easy to avoid the '*' operator:
mov eax, 1234h
mov edx, 5678h
imul edx
No '*' in sight. Of course, if you wanted to get into the spirit of it, you could also use the trusty old shift and add algorithm:
mult proc
; Multiplies eax by ebx and places result in edx:ecx
xor ecx, ecx
xor edx, edx
mul1:
test ebx, 1
jz mul2
add ecx, eax
adc edx, 0
mul2:
shr ebx, 1
shl eax, 1
test ebx, ebx
jnz mul1
done:
ret
mult endp
Of course, with modern processors, all (?) have multiplication instructions, but back when the PDP-11 was shiny and new, code like this saw real use.
Mathematically speaking, multiplication distributes over addition. Essentially, this means:
x * (a + b + c ...) = (x * a) + (x * b) + (x * c) ...
Any real number (in your case 7), can be presented as a series of additions (such as 8 + (-1), since subtraction is really just addition going the wrong way). This allows you to represent any single multiplication statement as an equivalent series of multiplication statements, which will come up with the same result:
x * 7
= x * (8 + (-1))
= (x * 8) + (x * (-1))
= (x * 8) - (x * 1)
= (x * 8) - x
The bitwise shift operator essentially just multiplies or divides a number by a power of 2. So long as your equation is only dealing with such values, bit shifting can be used to replace all occurrence of the multiplication operator.
(x * 8) - x = (x * 23) - x = (x << 3) - x
A similar strategy can be used on any other integer, and it makes no difference whether it's odd or even.
It is the same as x*8-x = x*(8-1) = x*7
Any number, odd or even, can be expressed as a sum of powers of two. For example,
1 2 4 8
------------------
1 = 1
2 = 0 + 2
3 = 1 + 2
4 = 0 + 0 + 4
5 = 1 + 0 + 4
6 = 0 + 2 + 4
7 = 1 + 2 + 4
8 = 0 + 0 + 0 + 8
11 = 1 + 2 + 0 + 8
So, you can multiply x by any number by performing the right set of shifts and adds.
1x = x
2x = 0 + x<<1
3x = x + x<<1
4x = 0 + 0 + x<<2
5x = x + 0 + x<<2
11x = x + x<<1 + 0 + x<<3
When it comes down to it, multiplication by a positive integer can be done like this:
int multiply(int a, int b) {
int ret = 0;
for (int i=0; i<b; i++) {
ret += b;
}
return ret;
}
Efficient? Hardly. But it's correct (factoring in limits on ints and so forth).
So using a left-shift is just a shortcut for multiplying by 2. But once you get to the highest power-of-2 under b you just add a the necessary number of times, so:
int multiply(int a, int b) {
int ret = a;
int mult = 1;
while (mult <= b) {
ret <<= 1;
mult <<= 1;
}
while (mult < b) {
ret += a;
}
return ret;
}
or something close to that.
To put it another way, to multiply by 7.
Left shift by 2 (times 4). Left shift 3 is 8 which is >7;
Add b 3 times.
One evening, I found that I was extremely bored, and cooked this up:
#include <iostream>
typedef unsigned int uint32;
uint32 add(uint32 a, uint32 b) {
do {
uint32 s = a ^ b;
uint32 c = a & b;
a = s;
b = c << 1;
} while (a & b)
return (a | b)
}
uint32 mul(uint32 a, uint32 b) {
uint32 total = 0;
do {
uint32 s1 = a & (-(b & 1))
b >>= 1; a <<= 1;
total = add(s1, total)
} while (b)
return total;
}
int main(void) {
using namespace std;
uint32 a, b;
cout << "Enter two numbers to be multiplied: ";
cin >> a >> b;
cout << "Total: " << mul(a,b) << endl;
return 0;
}
The code above should be quite self-explanatory, as I tried to keep it as simple as possible. It should work, more or less, the way a CPU might perform these operations. The only bug I'm aware of is that a is not permitted to be greater than 32,767 and b is not permitted to be large enough to overflow a (that is, multiply overflow is not handled, so 64-bit results are not possible). It should even work with negative numbers, provided the inputs are appropriately reinterpret_cast<>.
O(log(b)) method
public int multiply_optimal(int a, int b) {
if (a == 0 || b == 0)
return 0;
if (b == 1)
return a;
if ((b & 1) == 0)
return multiply_optimal(a + a, b >> 1);
else
return a + multiply_optimal(a + a, b >> 1);
}
The resursive code works as follows:
Base case:
if either of the number is 0 ,product is 0.
if b=1, product =a.
If b is even:
ab can be written as 2a(b/2)
2a(b/2)=(a+a)(b/2)=(a+a)(b>>1) where'>>' arithematic right shift operator in java.
If b is odd:
ab can be written as a+a(b-1)
a+a(b-1)=a+2a(b-1)/2=a+(a+a)(b-1)/2=a+(a+a)((b-1)>>1)
Since b is odd (b-1)/2=b/2=b>>1
So ab=a+(2a*(b>>1))
NOTE:each recursive call b is halved => O(log(b))
unsigned int Multiply(unsigned int m1, unsigned int m2)
{
unsigned int numBits = sizeof(unsigned int) * 8; // Not part of the core algorithm
unsigned int product = 0;
unsigned int mask = 1;
for(int i =0; i < numBits; ++i, mask = mask << 1)
{
if(m1 & mask)
{
product += (m2 << i);
}
}
return product;
}
#Wang, that's a good generalization. But here is a slightly faster version. But it assumes no overflow and a is non-negative.
int mult(int a, int b){
int p=1;
int rv=0;
for(int i=0; a >= p && i < 31; i++){
if(a & p){
rv += b;
}
p = p << 1;
b = b << 1;
}
return rv;
}
It will loop at most 1+log_2(a) times. Could be faster if you swap a and b when a > b.
import java.math.BigInteger;
public class MultiplyTest {
public static void main(String[] args) {
BigInteger bigInt1 = new BigInteger("5");
BigInteger bigInt2 = new BigInteger("8");
System.out.println(bigInt1.multiply(bigInt2));
}
}
Shift and add doesn't work (even with sign extension) when the multiplicand is negative. Signed multiplication has to be done using Booth encoding:
Starting from the LSB, a change from 0 to 1 is -1; a change from 1 to 0 is 1, otherwise 0. There is also an implicit extra bit 0 below the LSB.
For example, the number 5 (0101) will be encoded as: (1)(-1)(1)(-1). You can verify this is correct:
5 = 2^3 - 2^2 + 2 -1
This algorithm also works with negative numbers in 2's complement form:
-1 in 4-bit 2's complement is 1111. Using the Booth algorithm: (1)(0)(0)(0)(-1), where there is no space for the leftmost bit 1 so we get: (0)(0)(0)(-1) which is -1.
/* Multiply two signed integers using the Booth algorithm */
int booth(int x, int y)
{
int prev_bit = 0;
int result = 0;
while (x != 0) {
int current_bit = x & 0x1;
if (prev_bit & ~current_bit) {
result += y;
} else if (~prev_bit & current_bit) {
result -= y;
}
prev_bit = current_bit;
x = static_cast<unsigned>(x) >> 1;
y <<= 1;
}
if (prev_bit)
result += y;
return result;
}
The above code does not check for overflow. Below is a slightly modified version that multiplies two 16 bit numbers and returns a 32 bit number so it never overflows:
/* Multiply two 16-bit signed integers using the Booth algorithm */
/* Returns a 32-bit signed integer */
int32_t booth(int16_t x, int16_t y)
{
int16_t prev_bit = 0;
int16_t sign_bit = (x >> 16) & 0x1;
int32_t result = 0;
int32_t y1 = static_cast<int32_t>(y);
while (x != 0) {
int16_t current_bit = x & 0x1;
if (prev_bit & ~current_bit) {
result += y1;
} else if (~prev_bit & current_bit) {
result -= y1;
}
prev_bit = current_bit;
x = static_cast<uint16_t>(x) >> 1;
y1 <<= 1;
}
if (prev_bit & ~sign_bit)
result += y1;
return result;
}
unsigned int Multiply( unsigned int a, unsigned int b )
{
int ret = 0;
// For each bit in b
for (int i=0; i<32; i++) {
// If that bit is not equal to zero
if (( b & (1 << i)) != 0) {
// Add it to our return value
ret += a << i;
}
}
return ret;
}
I avoided the sign bit, because it's kind of not the subject of the post. This is an implementation of what Wayne Conrad said basically. Here is another problem is you want to try more low level math operations. Project Euler is cool!
If you can use the log function:
public static final long multiplyUsingShift(int a, int b) {
int absA = Math.abs(a);
int absB = Math.abs(b);
//Find the 2^b which is larger than "a" which turns out to be the
//ceiling of (Log base 2 of b) == numbers of digits to shift
double logBase2 = Math.log(absB) / Math.log(2);
long bits = (long)Math.ceil(logBase2);
//Get the value of 2^bits
long biggerInteger = (int)Math.pow(2, bits);
//Find the difference of the bigger integer and "b"
long difference = biggerInteger - absB;
//Shift "bits" places to the left
long result = absA<<bits;
//Subtract the "difference" "a" times
int diffLoop = Math.abs(a);
while (diffLoop>0) {
result -= difference;
diffLoop--;
}
return (a>0&&b>0 || a<0&&b<0)?result:-result;
}
If you cannot use the log function:
public static final long multiplyUsingShift(int a, int b) {
int absA = Math.abs(a);
int absB = Math.abs(b);
//Get the number of bits for a 2^(b+1) larger number
int bits = 0;
int bitInteger = absB;
while (bitInteger>0) {
bitInteger /= 2;
bits++;
}
//Get the value of 2^bit
long biggerInteger = (int)Math.pow(2, bits);
//Find the difference of the bigger integer and "b"
long difference = biggerInteger - absB;
//Shift "bits" places to the left
long result = absA<<bits;
//Subtract the "difference" "a" times
int diffLoop = absA;
while (diffLoop>0) {
result -= difference;
diffLoop--;
}
return (a>0&&b>0 || a<0&&b<0)?result:-result;
}
I found this to be more efficient:
public static final long multiplyUsingShift(int a, int b) {
int absA = Math.abs(a);
int absB = Math.abs(b);
long result = 0L;
while (absA>0) {
if ((absA&1)>0) result += absB; //Is odd
absA >>= 1;
absB <<= 1;
}
return (a>0&&b>0 || a<0&&b<0)?result:-result;
}
and yet another way.
public static final long multiplyUsingLogs(int a, int b) {
int absA = Math.abs(a);
int absB = Math.abs(b);
long result = Math.round(Math.pow(10, (Math.log10(absA)+Math.log10(absB))));
return (a>0&&b>0 || a<0&&b<0)?result:-result;
}
In C#:
private static string Multi(int a, int b)
{
if (a == 0 || b == 0)
return "0";
bool isnegative = false;
if (a < 0 || b < 0)
{
isnegative = true;
a = Math.Abs(a);
b = Math.Abs(b);
}
int sum = 0;
if (a > b)
{
for (int i = 1; i <= b; i++)
{
sum += a;
}
}
else
{
for (int i = 1; i <= a; i++)
{
sum += b;
}
}
if (isnegative == true)
return "-" + sum.ToString();
else
return sum.ToString();
}
JAVA:Considering the fact, that every number can be splitted into powers of two:
1 = 2 ^ 0
2 = 2 ^ 1
3 = 2 ^ 1 + 2 ^ 0
...
We want to get x where:
x = n * m
So we can achieve that by doing following steps:
1. while m is greater or equal to 2^pow:
1.1 get the biggest number pow, such as 2^pow is lower or equal to m
1.2 multiply n*2^pow and decrease m to m-2^pow
2. sum the results
Sample implementation using recursion:
long multiply(int n, int m) {
int pow = 0;
while (m >= (1 << ++pow)) ;
pow--;
if (m == 1 << pow) return (n << pow);
return (n << pow) + multiply(n, m - (1 << pow));
}
I got this question in last job interview and this answer was accepted.
EDIT: solution for positive numbers
This is the simplest C99/C11 solution for positive numbers:
unsigned multiply(unsigned x, unsigned y) { return sizeof(char[x][y]); }
Another thinking-outside-the-box answer:
BigDecimal a = new BigDecimal(123);
BigDecimal b = new BigDecimal(2);
BigDecimal result = a.multiply(b);
System.out.println(result.intValue());
public static int multiply(int a, int b)
{
int temp = 0;
if (b == 0) return 0;
for (int ii = 0; ii < abs(b); ++ii) {
temp = temp + a;
}
return b >= 0 ? temp : -temp;
}
public static int abs(int val) {
return val>=0 ? val : -val;
}
public static void main(String[] args) {
System.out.print("Enter value of A -> ");
Scanner s=new Scanner(System.in);
double j=s.nextInt();
System.out.print("Enter value of B -> ");
Scanner p=new Scanner(System.in);
double k=p.nextInt();
double m=(1/k);
double l=(j/m);
System.out.print("Multiplication of A & B=> "+l);
}
package com.amit.string;
// Here I am passing two values, 7 and 3 and method getResult() will
// return 21 without use of any operator except the increment operator, ++.
//
public class MultiplyTwoNumber {
public static void main(String[] args) {
int a = 7;
int b = 3;
System.out.println(new MultiplyTwoNumber().getResult(a, b));
}
public int getResult(int i, int j) {
int result = 0;
// Check for loop logic it is key thing it will go 21 times
for (int k = 0; k < i; k++) {
for (int p = 0; p < j; p++) {
result++;
}
}
return result;
}
}
Loop it. Run a loop seven times and iterate by the number you are multiplying with seven.
Pseudocode:
total = 0
multiply = 34
loop while i < 7
total = total + multiply
endloop
A JavaScript approach for positive numbers
function recursiveMultiply(num1, num2){
const bigger = num1 > num2 ? num1 : num2;
const smaller = num1 <= num2 ? num1 : num2;
const indexIncrement = 1;
const resultIncrement = bigger;
return recursiveMultiplyHelper(bigger, smaller, 0, indexIncrement, resultIncrement)
}
function recursiveMultiplyHelper(num1, num2, index, indexIncrement, resultIncrement){
let result = 0;
if (index === num2){
return result;
}
if ((index+indexIncrement+indexIncrement) >= num2){
indexIncrement = 1;
resultIncrement = num1;
} else{
indexIncrement += indexIncrement;
resultIncrement += resultIncrement;
}
result = recursiveMultiplyHelper(num1, num2, (index+indexIncrement), indexIncrement, resultIncrement);
result += resultIncrement;
console.log(num1, num2, index, result);
return result;
}
Think about the normal multiplication method we use
1101 x =>13
0101 =>5
---------------------
1101
0000
1101
0000
===================
1000001 . => 65
Writing the same above in the code
#include<stdio.h>
int multiply(int a, int b){
int res = 0,count =0;
while(b>0) {
if(b & 0x1)
res = res + (a << count);
b = b>>1;
count++;
}
return res;
}
int main() {
printf("Sum of x+y = %d", multiply(5,10));
return 0;
}
Very simple, pal... Each time when you left shift a number it means you are multiplying the number by 2 which means the answer is (x<<3)-x.
To multiply of two numbers without * operator:
int mul(int a,int b) {
int result = 0;
if(b > 0) {
for(int i=1;i<=b;i++){
result += a;
}
}
return result;
}

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