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Store array of settings into database row

I want to optimize into database row application settings. Something like this
10 - enabled option 1;
12 - enabled option 2;
13 - enabled option 3;
And the entire number is stored into database as 1073741823.
I tried to implement this:
public void test() {
// Let's say you get a String representing your option from your database
String optionFromDB= "132456";
// optionFromDB is a number like "132456"
// We transform it to bigDecimal:
BigDecimal myOptions=new BigDecimal(optionFromDB);
// Then we can use it.
// enable the option X (X is a number)
myOptions.setBit(2);
// Disable option X
myOptions.clearBit(2);
// Save the options to the db:
String newValToSave=myOptions.toString();
// do something if option x enable:
if (myOptions.testBit(123)){
System.out.println("test");
}
}
How I can implement this properly?

Assume value is an integer - this will give you 32 options. If that's not enough, you can take long (64 bits) or apply the same logic to any number of bits.
To enable bit n: value |= 1 <<< n
To disable bit n: value &= ~(1 <<< n)
To test bit n: (value & (1 <<< n)) != 0
To convert to string: String s = Integer.toString(value)
To convert from string: value = Integer.parseInt(s)

Well, just use a number, let's call it state. The type should be decided according to the number of options that you will have. For instance if you have 10 options, Integer is more than enough. For each option you can use one bit of this integer state.
So to set the first option just set first bit, and in general the ith bit for the ith option. To see if the ith option is enabled check if the ith bit of the state is set.
Code key points
For setting the ith bit you can use the following code:
state |= 1 << i;
For testing the ith bit the following:
state & (1L << i)) != 0;
For clearing the ith bit use:
state &= ~(1 << i);

Could someone please explain how shifting is used in this code?

I'm solving sample problems while simultaneously trying to learn Python %\ ... but the problem book I got has problems and solutions in Java, so I'm trying to convert back and forth between the two languages. I just learned how bit shifting works and I've been staring at this code trying to figure out what exactly is going on here on line 5 (and 8) ... I tried writing down some examples just going through the code line by line but for some reason it's still not entirely obvious to me ...
Could someone please clarify?
Also, it's really strange to me that str.charAt(i) returns a character, as far as I understand, and you can then proceed to subtract it from another character like numbers ... Is applying int to a character the same as ord() in Python?
Problem: Implement an algorithm to determine is a string has all unique characters.
Solution (in the case with only characters a-z):
1 boolean isUniqueChars(String str){
2 int checker = 0
3 for (int i = 0; i < str.length(); i++){
4 int val = str.charAt(i) - 'a';
5 if ((checker & (1 << val)) > 0){
6 return false;
7 }
8 checker |= (1 << val);
9 }
10 return true;
11 }

Sure. This code will really only work if str has only lower case letters in it.
checker is a 32-bit integer, and you're using 26 of the 32 bits to record the presence of a particular letter in str. So bit 0 will be used to record the presence of a, bit 1 will be used to record the presence of b, and so on up to bit 25, which will be used to record the presence of z.
The basic algorithm is to work through str, character by character. For each character, find the corresponding bit in checker. If it's already been set, this character must be occurring for the second time - so we can stop processing and return false. Otherwise, set that bit.
If you get to the end of the string without finding any duplicate characters, then return true.
The magic is in the following steps.
Subtracting 'a' from each character converts it to a number from 0 to 25.
The symbol << is the "left shift" operator, which moves a bit pattern a number of bits to the left. The result of this is that 1 << val is the place value of a particular bit (1, 2, 4, 8 etc).
The symbol & does a binary AND, so the expression checker & (1 << val) will be 0 if bit val is cleared, or equal to 1 << val if it is set.
The symbol |= does a binary OR, and assigns the result to the variable on the left. So the expression checker |= (1 << val) sets bit val.

Let's try a simpler variation:
boolean isUniqueChars(String str) {
boolean[] seen = new boolean[26];
for (int i = 0; i < str.length(); i++) {
// convert char to 0-based offset
int index = str.charAt(i) - 'a';
if (seen[index]) {
// this char was seen already
return false;
}
seen[index] = true;
}
// no duplicates found
return true;
}
Pretty straighforward, right? We create a boolean array, using the character offset as an index, and check each character in the string to see if we've come across it yet. The code you posted uses the same logic, but with a more efficient bit set instead.
(1 << val) turns val into a bit index. checker & (1 << val) filters out other indexes so we can check just this one. (checker & (1 << val)) > 0 checks if there's any value at the index. checker |= (1 << val) turns the bit on at the index. All of the other logic is identical.

First, the code will only work reliably if the input string contains letters 'a' to 'z'.
The variable checker is a 32 bit int. Each bit in checker is used as a flag to indicate the presence of one of the 26 letters 'a' to 'z'.
The line
int val = str.charAt(i) - 'a';
converts the character stored at str index i into an integer stored in val, by subtracting the value of character 'a' so. Yes I think pascal has the Ord('') function which does the same.
a = 0
b = 1
c = 2
etc
etc
etc
z = 25
the code
(1 << val)
shifts val into the appropriate value for its bit position,
so
a = 0 = 1
b = 1 = 2
c = 2 = 4
d = 3 = 8
etc
etc
z = 25 = 33554432
if ((checker & (1 << val)) > 0)
determines if the bit is already set in checker, indicating a duplicate character. If so the function returns false.
else
checker |= (1 << val)
sets the bit in checker via a binary OR and then loops round again.

How to find if two numbers are consecutive numbers in gray code sequence

I am trying to come up with a solution to the problem that given two numbers, find if they are the consecutive numbers in the gray code sequence i.e., if they are gray code neighbors assuming that the gray code sequence is not mentioned.
I searched on various forums but couldn't get the right answer. It would be great if you can provide a solution for this.
My attempt to the problem - Convert two integers to binary and add the digits in both the numbers separately and find the difference between the sum of the digits in two numbers. If the difference is one then they are gray code neighbors.
But I feel this wont work for all cases. Any help is highly appreciated. Thanks a lot in advance!!!

Actually, several of the other answers seem wrong: it's true that two binary reflected Gray code neighbours differ by only one bit (I assume that by « the » Gray code sequence, you mean the original binary reflected Gray code sequence as described by Frank Gray). However, that does not mean that two Gray codes differing by one bit are neighbours (a => b does not mean that b => a). For example, the Gray codes 1000 and 1010 differ by only one bit but are not neighbours (1000 and 1010 are respectively 15 and 12 in decimal).
If you want to know whether two Gray codes a and b are neighbours, you have to check whether previous(a) = b OR next(a) = b. For a given Gray code, you get one neighbour by flipping the rightmost bit and the other neighbour bit by flipping the bit at the left of the rightmost set bit. For the Gray code 1010, the neighbours are 1011 and 1110 (1000 is not one of them).
Whether you get the previous or the next neighbour by flipping one of these bits actually depends on the parity of the Gray code. However, since we want both neighbours, we don't have to check for parity. The following pseudo-code should tell you whether two Gray codes are neighbours (using C-like bitwise operations):
function are_gray_neighbours(a: gray, b: gray) -> boolean
return b = a ^ 1 OR
b = a ^ ((a & -a) << 1)
end
Bit trick above: a & -a isolates the rigthmost set bit in a number. We shift that bit by one position to the left to get the bit we need to flip.

Assumptions:
Inputs a and b are grey code sequences in binary reflected gray code.
i.e a's and b's bit encoding is binary gray code representations.
#convert from greycode bits into regular binary bits
def gTob(num): #num is binary graycode
mask = num >> 1
while mask!=0:
num = num^mask
mask >>= 1
return num; #num is converted
#check if a and b are consecutive gray code encodings
def areGrayNeighbors(a,b):
return abs(gTob(a) - gTob(b)) == 1
Few Test cases:
areGrayNeighbors(9,11) --> True (since (1001, 1011) differ in only one
bit and are consecutive numbers in decimal representation)
areGrayNeighbors(9,10) --> False
areGrayNeighbors(14,10) --> True
References:
method gTob() used above is from rodrigo in this post The neighbors in Gray code

public int checkConsecutive2(int b1, int b2){
int x = (b1 ^ b2);
if((x & (x - 1)) !=0){
return 0;
}else{
return 1;
}
}

If two numbers are in gray code sequence, they differ by one binary digit. i.e the exclusive OR on the two numbers returns a power of 2. So, find XOR and check if the result is a power of two.
This solution works well for the all the test cases written by CodeKaichu above. I would love to know if it fails in any cases.
public boolean grayCheck(int x, int y) {
int z = x^y;
return (z&z-1)==0;
}

An obvious answer, but it works.
Convert each gray code into its respective Binary form, subtract the two. If you answer is a binary equivalent of +1 or -1 then the two gray codes are adjacent.
This seems like an over kill, but when you're siting in an interview and don't know the correct method, this works. Also to optimize, one can check the single bit difference filter, so we don't waste time converting and subtracting numbers that we know for sure aren't adjacent.

If you just want to check if the input numbers differ by just one bit:
public boolean checkIfDifferByOneBit(int a, int b){
int diff = 0;
while(a > 0 && b > 0){
if(a & 1 != b & 1)
diff++;
a = a >> 1;
b = b >> 1;
}
if (a > 0 || b > 0) // a correction in the solution provided by David Jones
return diff == 0 // In the case when a or b become zero before the other
return diff == 1;
}

You can check if two numbers differ by one bit or not as follows. In this method, difference in the length of binary numbers are taken care of. Eg, the output for 11 (1011) and 3 (11) will be returned as true.
Also, this does not solve the second criteria for Gray code adjacency. But if you only want to check if the numbers differ by one bit, the code below will help.
class Graycode{
public static boolean graycheck(int one, int two){
int differences = 0;
while (one > 0 || two > 0){
// Checking if the rightmost bit is same
if ((one & 1) != (two & 1)){
differences++;
}
one >>= 1;
two >>= 1;
}
return differences == 1;
}
public static void main(String[] args){
int one = Integer.parseInt(args[0]);
int two = Integer.parseInt(args[1]);
System.out.println(graycheck(one,two));
}
}

If two numbers are in gray code sequence, they differ by one binary digit. i.e the exclusive OR on the two numbers returns a power of 2. So, find XOR and check if the result is a power of two.
python 3.8
a=int(input())
b=int(input())
x=a^b
if((x and (not(x & (x - 1))) )):
print("True")
else:
print("False")

I've had to solve this question in an interview as well. One of the conditions for the two values to be a gray code sequence is that their values only differ by 1 bit. Here is a solution to this problem:
def isGrayCode(num1, num2):
differences = 0
while (num1 > 0 or num2 > 0):
if ((num1 & 1) != (num2 & 1)):
differences++
num1 >>= 1
num2 >>= 1
return differences == 1

How can I extract a particular bit in Java?

I need a specific bit in a byte value stored as int value. My code is as shown below.
private int getBitValue(int byteVal, int bitShift){
byteVal = byteVal << bitShift;
int bit = (int) (byteVal >>>7);
return bit;
}
It is working when I give the bitshift as 1 but when I give the bitshift as 2 and the byteVal as 67(01000011 in binary), I get the value of 'byteVal' as 268 while 'byteVal' should be 3(000011 in binary) after the first line in the method(the left shift). What am I doing wrong here?

For some reason when I try your code I don't get what you get. For your example, if you say byteVal = 0b01000011 and bitShift = 2, then this is what I get:
byteVal = 0b01000011 << 2 = 0b0100001100
bit = (int) (0b0100001100 >>> 7) = (int) (0b010) // redundant cast
returned value: 0b010 == 2
I believe what you intended to do was shift the bit you wanted to the leftmost position, and then shift it all the way to the right to get the bit. However, your code won't do that for a few reasons:
You need to shift left by (variable length - bitShift) to get the desired bit to the place you want. So in this case, what you really want is to shift byteVal left by 6 places, not 2.
int variables are 32 bits wide, not 8. (so you actually want to shift byteVal left by 30 places)
In addition, your question appears to be somewhat contradictory. You state you want a specific bit, yet your example implies you want the bitShift-th least significant bits.
An easier way of getting a specific bit might be to simply shift right as far as you need and then mask with 1: (also, you can't use return with void, but I'm assuming that was a typo)
private int getBitValue(int byteVal, int bitShift) {
byteVal = byteVal >> bitShift; // makes the bitShift-th bit the rightmost bit
// Assumes bit numbers are 0-based (i.e. original rightmost bit is the 0th bit)
return (int) (byteVal & 1) // AND the result with 1, which keeps only the rightmost bit
}
If you want the bitShift-th least significant bits, I believe something like this would work:
private int getNthLSBits(int byteVal, int numBits) {
return byteVal & ((1 << numBits) - 1);
// ((1 << numBits) - 1) gives you numBits ones
// i.e. if numBits = 3, (1 << numBits) - 1 == 0b111
// AND that with byteVal to get the numBits-th least significant bits
}

I'm curious why the answer should be 3 and I think we need more information on what the function should do.
Assuming you want the value of the byteVal's lowest bitShift bits, I'd do the following.
private int getBitValue(int byteVal, int bitShift){
int mask = 1 << bitShift; // mask = 1000.... (number of 0's = bitShift)
mask--; // mask = 000011111 (number of 1's = bitShift)
return (byteVal & mask);
}
At the very least, this function will return 1 for getBitValue(67, 1) and 3 for getBitValue(67,2).

signed to positive near-perfect hash

I have an integer type, say long, whose values are between Long.MIN_VALUE = 0x80...0 (-2^63) and Long.MAX_VALUE = 0x7f...f (2^63 - 1). I want to hash it with ~50% collision to a positive integer of the same type (i.e. between 1 and Long.MAX_VALUE) in a clean and efficient manner.
My first attempts were something like:
Math.abs(x) + 1
(x & Long.MAX_VALUE) + 1
but those and similar approaches always have problems with certain values, i.e. when x is 0 / Long.MIN_VALUE / Long.MAX_VALUE. Of course, the naive solution is to use 2 if statements, but I'm looking for something cleaner / shorter / faster. Any ideas?
Note: Assume that I'm working in Java where there is no implicit conversion to boolean and shift semantics is defined.

The simplest approach is to zero the sign bit and then map zero to some other value:
Long y = x & Long.MAX_VALUE;
return (y == 0)? 42: y;
This is simple, uses only one if/ternary operator, and gives ~50% collision rate on average. There is one disadvantage: it maps 4 different values (0, 42, MIN_VALUE, MIN_VALUE+42) to one value (42). So for this value we have 75% collisions, while for other values - exactly 50%.
It may be preferable to distribute collisions more evenly:
return (x == 0)? 42: (x == Long.MIN_VALUE) ? 142: x & Long.MAX_VALUE;
This code gives 67% collisions for 2 values and 50% for other values. You cannot distribute collisions more evenly, but it is possible to choose these 2 most colliding values. Disadvantage is that this code uses two ifs/ternary operators.
It is possible to avoid 75% collisions on single value while using only one if/ternary operator:
Long y = x & Long.MAX_VALUE;
return (y == 0)? 42 - (x >> 7): y;
This code gives 67% collisions for 2 values and 50% collisions for other values. There is less freedom choosing these most colliding values: 0 maps to 42 (and you can choose almost any value instead); MIN_VALUE maps to 42 - (MIN_VALUE >> 7) (and you can shift MIN_VALUE by any value from 1 to 63, only make sure that A - (MIN_VALUE >> B) does not overflow).
It is possible to get the same result (67% collisions for 2 values and 50% collisions for other values) without conditional operators (but with more complicated code):
Long y = x - 1 - ((x >> 63) << 1);
Long z = y + 1 + (y >> 63);
return z & Long.MAX_VALUE;
This gives 67% collisions for values '1' and 'MAX_VALUE'. If it is more convenient to get most collisions for some other values, just apply this algorithm to x + A, where 'A' is any number.
An improved variant of this solution:
Long y = x + 1 + ((x >> 63) << 1);
Long z = y - (y >> 63);
return z & Long.MAX_VALUE;

Assuming you want to collapse all values into the positive space, why not just zero the sign bit?
You can do this with a single bitwise op by taking advantage of the fact that MAX_VALUE is just a zero sign bit followed by ones e.g.
int positive = value & Integer.MAX_VALUE;
Or for longs:
long positive = value & Long.MAX_VALUE;
If you want a "better" hash with pseudo-random qualities, you probably want to pss the value through another hash function first. My favourite fast hashes are the XORshift family by George Marsaglia. These have the nice property that they map the entire int / long number space perfectly onto itself, so you will still get exactly 50% collisions after zeroing the sign bit.
Here's a quick XORshift implementation in Java:
public static final long xorShift64(long a) {
a ^= (a << 21);
a ^= (a >>> 35);
a ^= (a << 4);
return a;
}
public static final int xorShift32(int a) {
a ^= (a << 13);
a ^= (a >>> 17);
a ^= (a << 5);
return a;
}

I would opt for the most simple, yet not totally time wasting version:
public static long postiveHash(final long hash) {
final long result = hash & Long.MAX_VALUE;
return (result != 0) ? result : (hash == 0 ? 1 : 2);
}
This implementation pays one conditional operation for all but two possible inputs: 0 and MIN_VALUE. Those two are assigned different value mappings with the second condition. I doubt you get a better combination of (code) simplicity and (computational) complexity.
Of course if you can live with a worse distribution, it gets a lot simpler. By restricting the space to 1/4 instead of to 1/2 -1 you can get:
public static long badDistribution(final long hash) {
return (hash & -4) + 1;
}

You can do it without any conditionals and in a single expression by using the unsigned shift operator:
public static int makePositive(int x) {
return (x >>> 1) + (~x >>> 31);
}

If the value is positive, it probably can be used directly, else, invert all bits:
x >= 0 ? hash = x : hash = x ^ Long.MIN_VALUE
However, you should scramble this value a bit more if the values of x are correlated (meaning: similar objects produce similar values for x), maybe with
hash = a * (hash + b) % (Long.MAX_VALUE) + 1
for some positive constants a and b, where a should be quite large and b prevents that 0 is always mapped to 1. This also maps the whole thing to [1,Long.MAX_VALUE] instead of [0,Long.MAX_VALUE]. By altering the values for a and b you could also implement more complex hash functionalities like cooko hashing, that needs two different hash functions.
Such a solution should definitely be preferred instead of one that delivers "strange collision distribution" for the same values each time it is used.

From the information theoretic view, you have 2^64 values to map into 2^63-1 values.
As such, mapping is trivial with the modulus operator, since it always has a non-negative result:
y = 1 + x % 0x7fffffffffffffff; // the constant is 2^63-1
This could be pretty expensive, so what else is possible?
The simple math 2^64 = 2 * (2^63 - 1) + 2 says we will have two source values mapping to one target value except in two special cases, where three will go to one. Think of these as two special 64-bit values, call them x1 and x2, that each share a target with two other source values. In the mod expression above, this occurs by "wrapping". The target values y=2^31-2 and y=2^31-3 have three mappings. All others have two. Since we have to use something more complex than mod anyway, let's seek a way to map the special values wherever we like at low cost
For illustration let's work with mapping a 4-bit signed int x in [-8..7] to y in [1..7], rather than the 64-bit space.
An easy course is to have x values in [1..7] map to themselves, then the problem reduces to mapping x in [-8..0] to y in [1..7]. Note there are 9 source values here and only 7 targets as discussed above.
There are obviously many strategies. At this point you can probably see a gazzilion. I'll describe only one that's particularly simple.
Let y = 1 - x for all values except special cases x1 == -8 and x2 == -7. The whole hash function thus becomes
y = x <= -7 ? S(x) : x <= 0 ? 1 - x : x;
Here S(x) is a simple function that says where x1 and x2 are mapped. Choose S based on what you know about the data. For example if you think high target values are unlikely, map them to 6 and 7 with S(x) = -1 - x.
The final mapping is:
-8: 7 -7: 6 -6: 7 -5: 6 -4: 5 -3: 4 -2: 3 -1: 2
0: 1 1: 1 2: 2 3: 3 4: 4 5: 5 6: 6 7: 7
Taking this logic up to the 64-bit space, you'd have
y = (x <= Long.MIN_VALUE + 1) ? -1 - x : x <= 0 ? 1 - x : x;
Many other kinds of tuning are possible within this framework.

Just to make sure, you have a long and want to hash it to an int?
You could do...
(int) x // This results in a meaningless number, but it works
(int) (x & 0xffffffffl) // This will give you just the low order bits
(int) (x >> 32) // This will give you just the high order bits
((Long) x).hashcode() // This is the high and low order bits XORed together
If you want to keep a long you could do...
x & 0x7fffffffffffffffl // This will just ignore the sign, Long.MIN_VALUE -> 0
x & Long.MAX_VALUE // Should be the same I think
If getting a 0 is no good...
x & 0x7ffffffffffffffel + 1 // This has a 75% collision rate.
Just thinking out loud...
((x & Long.MAX_VALUE) << 1) + 1 // I think this is also 75%
I think you're going to need to either be ok with 75% or get a little ugly:
(x > 0) ? x : (x < 0) ? x & Long.MAX_VALUE : 7

This seems the simplest of all:
(x % Long.MAX_VALUE) + 1
I would be interested in speed comparisons of all the methods given.

Just AND your input value with Long.MAX_VALUE and OR it with 1. Nothing else needed.
Ex:
long hash = (input & Long.MAX_VALUE) | 1;