Develop Reference

python equivalent for java byte negation [duplicate]

I'm a little confused by the ~ operator. Code goes below:
a = 1
~a #-2
b = 15
~b #-16
How does ~ do work?
I thought, ~a would be something like:
0001 = a
1110 = ~a
why not?

You are exactly right. It's an artifact of two's complement integer representation.
In 16 bits, 1 is represented as 0000 0000 0000 0001. Inverted, you get 1111 1111 1111 1110, which is -2. Similarly, 15 is 0000 0000 0000 1111. Inverted, you get 1111 1111 1111 0000, which is -16.
In general, ~n = -n - 1

The '~' operator is defined as:
"The bit-wise inversion of x is defined as -(x+1). It only applies to integral numbers."Python Doc - 5.5
The important part of this sentence is that this is related to 'integral numbers' (also called integers). Your example represents a 4 bit number.
'0001' = 1
The integer range of a 4 bit number is '-8..0..7'. On the other hand you could use 'unsigned integers', that do not include negative number and the range for your 4 bit number would be '0..15'.
Since Python operates on integers the behavior you described is expected. Integers are represented using two's complement. In case of a 4 bit number this looks like the following.
7 = '0111'
0 = '0000'
-1 = '1111'
-8 = '1000'
Python uses 32bit for integer representation in case you have a 32-bit OS. You can check the largest integer with:
sys.maxint # (2^31)-1 for my system
In case you would like an unsigned integer returned for you 4 bit number you have to mask.
'0001' = a # unsigned '1' / integer '1'
'1110' = ~a # unsigned '14' / integer -2
(~a & 0xF) # returns 14
If you want to get an unsigned 8 bit number range (0..255) instead just use:
(~a & 0xFF) # returns 254

It looks like I found simpler solution that does what is desired:
uint8: x ^ 0xFF
uint16: x ^ 0xFFFF
uint32: x ^ 0xFFFFFFFF
uint64: x ^ 0xFFFFFFFFFFFFFFFF

You could also use unsigned ints (for example from the numpy package) to achieve the expected behaviour.
>>> import numpy as np
>>> bin( ~ np.uint8(1))
'0b11111110'

The problem is that the number represented by the result of applying ~ is not well defined as it depends on the number of bits used to represent the original value. For instance:
5 = 101
~5 = 010 = 2
5 = 0101
~5 = 1010 = 10
5 = 00101
~5 = 11010 = 26
However, the two's complement of ~5 is the same in all cases:
two_complement(~101) = 2^3 - 2 = 6
two_complement(~0101) = 2^4 - 10 = 6
two_complement(~00101) = 2^5 - 26 = 6
And given that the two's complement is used to represent negative values, it makes sense to consider ~5 as the negative value, -6, of its complement.
So, more formally, to arrive at this result we have:
flipped zeros and ones (that's equivalent to taking the ones' complement)
taken two's complement
applied negative sign
and if x is a n-digit number:
~x = - two_complement(one_complement(x)) = - two_complement(2^n - 1 - x) = - (2^n - (2^n - 1 - x)) = - (x + 1)

binary maximum and minimum number limitation of int type in Java [duplicate]

I am trying to understand how Java stores integer internally. I know all java primitive integers are signed, (except short?). That means one less bit available in a byte for the number.
My question is, are all integers (positive and negative) stored as two's complement or are only negative numbers in two's complement?
I see that the specs says x bit two's complement number. But I often get confused.
For instance:
int x = 15; // Stored as binary as is? 00000000 00000000 00000000 00001111?
int y = -22; // Stored as two complemented value? 11111111 11111111 11111111 11101010
Edit
To be clear, x = 15
In binary as is: `00000000 00000000 00000000 00001111'
Two's complement: `11111111 11111111 11111111 11110001`
So if your answer is all numbers are stored as two's complement then:
int x = 15; // 11111111 11111111 11111111 11110001
int y = -22 // 11111111 11111111 11111111 11101010
The confusion here again is the sign says, both are negative numbers. May be I am misreading / misunderstanding it?
Edit
Not sure my question is confusing. Forced to isolate the question:
My question precisely: Are positive numbers stored in binary as is while negative numbers are stored as two's complement?
Some said all are stored in two's complement and one answer says only negative numbers are stored as two's complement.

Let's start by summarizing Java primitive data types:
byte: Byte data type is an 8-bit signed two's complement integer.
Short: Short data type is a 16-bit signed two's complement integer.
int: Int data type is a 32-bit signed two's complement integer.
long: Long data type is a 64-bit signed two's complement integer.
float: Float data type is a single-precision 32-bit IEEE 754 floating point.
double: double data type is a double-precision 64-bit IEEE 754 floating point.
boolean: boolean data type represents one bit of information.
char: char data type is a single 16-bit Unicode character.
Source
Two's complement
"The good example is from wiki that the relationship to two's complement is realized by noting that 256 = 255 + 1, and (255 − x) is the ones' complement of x
0000 0111=7 two's complement is 1111 1001= -7
the way it works is the MSB(the most significant bit) receives a negative value so in the case above
-7 = 1001= -8 + 0+ 0+ 1
Positive integers are generally stored as simple binary numbers (1 is 1, 10 is 2, 11 is 3, and so on).
Negative integers are stored as the two's complement of their absolute value. The two's complement of a positive number is when using this notation a negative number.
Source
Since I received a few points for this answer, I decided to add more information to it.
A more detailed answer:
Among others there are four main approaches to represent positive and negative numbers in binary, namely:
Signed Magnitude
One's Complement
Two's Complement
Bias
1. Signed Magnitude
Uses the most significant bit to represent the sign, the remaining bits are used to represent the absolute value. Where 0 represents a positive number and 1 represents a negative number, example:
1011 = -3
0011 = +3
This representation is simpler. However, you cannot add binary numbers in the same way that you add decimal numbers, making it harder to be implemented at the hardware level. Moreover, this approach uses two binary patterns to represent the 0, -0 (1000) and +0 (0000).
2. One's Complement
In this representation, we invert all the bits of a given number to find out its complementary. For example:
010 = 2, so -2 = 101 (inverting all bits).
The problem with this representation is that there still exist two bits patterns to represent the 0, negative 0 (1111) and positive 0 (0000)
3. Two's Complement
To find the negative of a number, in this representation, we invert all the bits and then add one bit. Adding one bit solves the problem of having two bits patterns representing 0. In this representation, we only have one pattern for
0 (0000).
For example, we want to find the binary negative representation of 4 (decimal) using 4 bits. First, we convert 4 to binary:
4 = 0100
then we invert all the bits
0100 -> 1011
finally, we add one bit
1011 + 1 = 1100.
So 1100 is equivalent to -4 in decimal if we are using a Two's Complement binary representation with 4 bits.
A faster way to find the complementary is by fixing the first bit that as value 1 and inverting the remaining bits. In the above example it would be something like:
0100 -> 1100
^^
||-(fixing this value)
|--(inverting this one)
Two's Complement representation, besides having only one representation for 0, it also adds two binary values in the same way that in decimal, even numbers with different signs. Nevertheless, it is necessary to check for overflow cases.
4. Bias
This representation is used to represent the exponent in the IEEE 754 norm for floating points. It has the advantage that the binary value with all bits to zero represents the smallest value. And the binary value with all bits to 1 represents the biggest value. As the name indicates, the value is encoded (positive or negative) in binary with n bits with a bias (normally 2^(n-1) or 2^(n-1)-1).
So if we are using 8 bits, the value 1 in decimal is represented in binary using a bias of 2^(n-1), by the value:
+1 + bias = +1 + 2^(8-1) = 1 + 128 = 129
converting to binary
1000 0001

Java integers are of 32 bits, and always signed. This means, the most significant bit (MSB) works as the sign bit. The integer represented by an int is nothing but the weighted sum of the bits. The weights are assigned as follows:
Bit# Weight
31 -2^31
30 2^30
29 2^29
... ...
2 2^2
1 2^1
0 2^0
Note that the weight of the MSB is negative (the largest possible negative actually), so when this bit is on, the whole number (the weighted sum) becomes negative.
Let's simulate it with 4-bit numbers:
Binary Weighted sum Integer value
0000 0 + 0 + 0 + 0 0
0001 0 + 0 + 0 + 2^0 1
0010 0 + 0 + 2^1 + 0 2
0011 0 + 0 + 2^1 + 2^0 3
0100 0 + 2^2 + 0 + 0 4
0101 0 + 2^2 + 0 + 2^0 5
0110 0 + 2^2 + 2^1 + 0 6
0111 0 + 2^2 + 2^1 + 2^0 7 -> the most positive value
1000 -2^3 + 0 + 0 + 0 -8 -> the most negative value
1001 -2^3 + 0 + 0 + 2^0 -7
1010 -2^3 + 0 + 2^1 + 0 -6
1011 -2^3 + 0 + 2^1 + 2^0 -5
1100 -2^3 + 2^2 + 0 + 0 -4
1101 -2^3 + 2^2 + 0 + 2^0 -3
1110 -2^3 + 2^2 + 2^1 + 0 -2
1111 -2^3 + 2^2 + 2^1 + 2^0 -1
So, the two's complement thing is not an exclusive scheme for representing negative integers, rather we can say that the binary representation of integers are always the same, we just negate the weight of the most significant bit. And that bit determines the sign of the integer.
In C, there is a keyword unsigned (not available in java), which can be used for declaring unsigned int x;. In the unsigned integers, the weight of the MSB is positive (2^31) rather than being negative. In that case the range of an unsigned int is 0 to 2^32 - 1, while an int has range -2^31 to 2^31 - 1.
From another point of view, if you consider the two's complement of x as ~x + 1 (NOT x plus one), here's the explanation:
For any x, ~x is just the bitwise inverse of x, so wherever x has a 1-bit, ~x will have a 0-bit there (and vice versa). So, if you add these up, there will be no carry in the addition and the sum will be just an integer every bit of which is 1.
For 32-bit integers:
x + ~x = 1111 1111 1111 1111 1111 1111 1111 1111
x + ~x + 1 = 1111 1111 1111 1111 1111 1111 1111 1111 + 1
= 1 0000 0000 0000 0000 0000 0000 0000 0000
The leftmost 1-bit will simply be discarded, because it doesn't fit in 32-bits (integer overflow). So,
x + ~x + 1 = 0
-x = ~x + 1
So you can see that the negative x can be represented by ~x + 1, which we call the two's complement of x.

I have ran the following program to know it
public class Negative {
public static void main(String[] args) {
int i =10;
int j = -10;
System.out.println(Integer.toBinaryString(i));
System.out.println(Integer.toBinaryString(j));
}
}
Output is
1010
11111111111111111111111111110110
From the output it seems that it has been using two's complement.

Oracle provides some documentation regarding Java Datatypes that you may find interesting. Specifically:
int: The int data type is a 32-bit signed two's complement integer. It has a minimum value of -2,147,483,648 and a maximum value of 2,147,483,647 (inclusive).
Btw, short is also stored as two's complement.

Positive numbers are stored/retrived as it is.
e.g) For +ve number 10; byte representation will be like 0-000 0010
(0 - MSB will represent that it is +ve).
So while retrieving based on MSB; it says it is +ve,
so the value will be taken as it is.
But negative numbers will be stored after 2's complement (other than
MSB bit), and MSB bit will be set to 1.
e.g) when storing -10 then
0-000 0010 -> (1's complement) -> 0-111 1101
-> (2's complement) 0-111 1101 + 1 -> 0-111 1110
Now MSB will be set to one, since it is negative no -> 1-111 1110
when retrieving, it found that MSB is set to 1. So it is negative no.
And 2's complement will be performed other than MSB.
1-111 1110 --> 1-000 0001 + 1 --> 1-000 0010
Since MSB representing this is negative 10 --> hence -10 will be retrived.
Casting
Also note that when you are casting int/short to byte, only last byte will be considered along with last byte MSB,
Take example "-130" short, it might be stored like below
(MSB)1-(2's complement of)130(1000 0010) --> 1-111 1111 0111 1110
Now byte casting took last byte which is 0111 1110. (0-MSB)
Since MSB says it is +ve value, so it will be taken as it is.
Which is 126. (+ve).
Take another example "130" short, it might be stored like below
0-000 000 1000 0010 (MSB = 0)
Now byte casting took last byte which is 1000 0010 . (1=MSB)
Since MSB says it is -ve value, 2's complement will be performed and negative number will be returned. So in this case -126 will be returned.
1-000 0010 -> (1's complement) -> 1-111 1101
-> (2's complement) 1-111 1101 + 1 -> 1-111 1110 -> (-)111 1110
= -126
Diff between (int)(char)(byte) -1 AND (int)(short)(byte) -1
(byte)-1 -> 0-000 0001 (2's Comp) -> 0-111 1111 (add sign) -> 1-111 1111
(char)(byte)-1 -> 1-111 1111 1111 1111 (sign bit is carry forwarded on left)
similarly
(short)(byte)-1-> 1-111 1111 1111 1111 (sign bit is carry forwarded on left)
But
(int)(char)(byte)-1 -> 0-0000000 00000000 11111111 11111111 = 65535
since char is unsigned; MSB won't be carry forwarded.
AND
(int)(Short)(byte)-1 -> 1-1111111 11111111 11111111 11111111 = -1
since short is signed; MSB is be carry forwarded.
References
Why is two's complement used to represent negative numbers?
What is “2's Complement”?

The most significant bit (32nd) indicates that the number is positive or negative. If it is 0, it means the number is positive and it is stored in its actual binary representation. but if it is 1, it means the number is negative and is stored in its two's complement representation. So when we give weight -2^32 to the 32nd bit while restoring the integer value from its binary representation, We get the actual answer.

According to this document, all integers are signed and stored in two's complement format for java. Not certain of its reliability..

positive numbers are stored directly as binary. 2's compliment is required for negative numbers.
for example:
15 : 00000000 00000000 00000000 00001111
-15: 11111111 11111111 11111111 11110001
here is the difference in signed bit.

Thank you, dreamcrash for the answer https://stackoverflow.com/a/13422442/1065835; on the wiki page they give an example which helped me understand how to find out the binary representation of the negative counterpart of a positive number.
For example, using 1 byte (= 2 nibbles = 8 bits), the decimal number 5
is represented by
0000 01012 The most significant bit is 0, so the pattern represents a
non-negative value. To convert to −5 in two's-complement notation, the
bits are inverted; 0 becomes 1, and 1 becomes 0:
1111 1010 At this point, the numeral is the ones' complement of the
decimal value −5. To obtain the two's complement, 1 is added to the
result, giving:
1111 1011 The result is a signed binary number representing the
decimal value −5 in two's-complement form. The most significant bit is
1, so the value represented is negative.

For positive integer 2'complement value is same with MSB bit 0 (like +14 2'complement is 01110).
For only negative integer only we are calculating 2'complement value (-14= 10001+1 = 10010).
So final answer is both the values(+ve and -ve) are stored in 2'complement form only.

How are integers internally represented at a bit level in Java?

I am trying to understand how Java stores integer internally. I know all java primitive integers are signed, (except short?). That means one less bit available in a byte for the number.
My question is, are all integers (positive and negative) stored as two's complement or are only negative numbers in two's complement?
I see that the specs says x bit two's complement number. But I often get confused.
For instance:
int x = 15; // Stored as binary as is? 00000000 00000000 00000000 00001111?
int y = -22; // Stored as two complemented value? 11111111 11111111 11111111 11101010
Edit
To be clear, x = 15
In binary as is: `00000000 00000000 00000000 00001111'
Two's complement: `11111111 11111111 11111111 11110001`
So if your answer is all numbers are stored as two's complement then:
int x = 15; // 11111111 11111111 11111111 11110001
int y = -22 // 11111111 11111111 11111111 11101010
The confusion here again is the sign says, both are negative numbers. May be I am misreading / misunderstanding it?
Edit
Not sure my question is confusing. Forced to isolate the question:
My question precisely: Are positive numbers stored in binary as is while negative numbers are stored as two's complement?
Some said all are stored in two's complement and one answer says only negative numbers are stored as two's complement.

Let's start by summarizing Java primitive data types:
byte: Byte data type is an 8-bit signed two's complement integer.
Short: Short data type is a 16-bit signed two's complement integer.
int: Int data type is a 32-bit signed two's complement integer.
long: Long data type is a 64-bit signed two's complement integer.
float: Float data type is a single-precision 32-bit IEEE 754 floating point.
double: double data type is a double-precision 64-bit IEEE 754 floating point.
boolean: boolean data type represents one bit of information.
char: char data type is a single 16-bit Unicode character.
Source
Two's complement
"The good example is from wiki that the relationship to two's complement is realized by noting that 256 = 255 + 1, and (255 − x) is the ones' complement of x
0000 0111=7 two's complement is 1111 1001= -7
the way it works is the MSB(the most significant bit) receives a negative value so in the case above
-7 = 1001= -8 + 0+ 0+ 1
Positive integers are generally stored as simple binary numbers (1 is 1, 10 is 2, 11 is 3, and so on).
Negative integers are stored as the two's complement of their absolute value. The two's complement of a positive number is when using this notation a negative number.
Source
Since I received a few points for this answer, I decided to add more information to it.
A more detailed answer:
Among others there are four main approaches to represent positive and negative numbers in binary, namely:
Signed Magnitude
One's Complement
Two's Complement
Bias
1. Signed Magnitude
Uses the most significant bit to represent the sign, the remaining bits are used to represent the absolute value. Where 0 represents a positive number and 1 represents a negative number, example:
1011 = -3
0011 = +3
This representation is simpler. However, you cannot add binary numbers in the same way that you add decimal numbers, making it harder to be implemented at the hardware level. Moreover, this approach uses two binary patterns to represent the 0, -0 (1000) and +0 (0000).
2. One's Complement
In this representation, we invert all the bits of a given number to find out its complementary. For example:
010 = 2, so -2 = 101 (inverting all bits).
The problem with this representation is that there still exist two bits patterns to represent the 0, negative 0 (1111) and positive 0 (0000)
3. Two's Complement
To find the negative of a number, in this representation, we invert all the bits and then add one bit. Adding one bit solves the problem of having two bits patterns representing 0. In this representation, we only have one pattern for
0 (0000).
For example, we want to find the binary negative representation of 4 (decimal) using 4 bits. First, we convert 4 to binary:
4 = 0100
then we invert all the bits
0100 -> 1011
finally, we add one bit
1011 + 1 = 1100.
So 1100 is equivalent to -4 in decimal if we are using a Two's Complement binary representation with 4 bits.
A faster way to find the complementary is by fixing the first bit that as value 1 and inverting the remaining bits. In the above example it would be something like:
0100 -> 1100
^^
||-(fixing this value)
|--(inverting this one)
Two's Complement representation, besides having only one representation for 0, it also adds two binary values in the same way that in decimal, even numbers with different signs. Nevertheless, it is necessary to check for overflow cases.
4. Bias
This representation is used to represent the exponent in the IEEE 754 norm for floating points. It has the advantage that the binary value with all bits to zero represents the smallest value. And the binary value with all bits to 1 represents the biggest value. As the name indicates, the value is encoded (positive or negative) in binary with n bits with a bias (normally 2^(n-1) or 2^(n-1)-1).
So if we are using 8 bits, the value 1 in decimal is represented in binary using a bias of 2^(n-1), by the value:
+1 + bias = +1 + 2^(8-1) = 1 + 128 = 129
converting to binary
1000 0001

Java integers are of 32 bits, and always signed. This means, the most significant bit (MSB) works as the sign bit. The integer represented by an int is nothing but the weighted sum of the bits. The weights are assigned as follows:
Bit# Weight
31 -2^31
30 2^30
29 2^29
... ...
2 2^2
1 2^1
0 2^0
Note that the weight of the MSB is negative (the largest possible negative actually), so when this bit is on, the whole number (the weighted sum) becomes negative.
Let's simulate it with 4-bit numbers:
Binary Weighted sum Integer value
0000 0 + 0 + 0 + 0 0
0001 0 + 0 + 0 + 2^0 1
0010 0 + 0 + 2^1 + 0 2
0011 0 + 0 + 2^1 + 2^0 3
0100 0 + 2^2 + 0 + 0 4
0101 0 + 2^2 + 0 + 2^0 5
0110 0 + 2^2 + 2^1 + 0 6
0111 0 + 2^2 + 2^1 + 2^0 7 -> the most positive value
1000 -2^3 + 0 + 0 + 0 -8 -> the most negative value
1001 -2^3 + 0 + 0 + 2^0 -7
1010 -2^3 + 0 + 2^1 + 0 -6
1011 -2^3 + 0 + 2^1 + 2^0 -5
1100 -2^3 + 2^2 + 0 + 0 -4
1101 -2^3 + 2^2 + 0 + 2^0 -3
1110 -2^3 + 2^2 + 2^1 + 0 -2
1111 -2^3 + 2^2 + 2^1 + 2^0 -1
So, the two's complement thing is not an exclusive scheme for representing negative integers, rather we can say that the binary representation of integers are always the same, we just negate the weight of the most significant bit. And that bit determines the sign of the integer.
In C, there is a keyword unsigned (not available in java), which can be used for declaring unsigned int x;. In the unsigned integers, the weight of the MSB is positive (2^31) rather than being negative. In that case the range of an unsigned int is 0 to 2^32 - 1, while an int has range -2^31 to 2^31 - 1.
From another point of view, if you consider the two's complement of x as ~x + 1 (NOT x plus one), here's the explanation:
For any x, ~x is just the bitwise inverse of x, so wherever x has a 1-bit, ~x will have a 0-bit there (and vice versa). So, if you add these up, there will be no carry in the addition and the sum will be just an integer every bit of which is 1.
For 32-bit integers:
x + ~x = 1111 1111 1111 1111 1111 1111 1111 1111
x + ~x + 1 = 1111 1111 1111 1111 1111 1111 1111 1111 + 1
= 1 0000 0000 0000 0000 0000 0000 0000 0000
The leftmost 1-bit will simply be discarded, because it doesn't fit in 32-bits (integer overflow). So,
x + ~x + 1 = 0
-x = ~x + 1
So you can see that the negative x can be represented by ~x + 1, which we call the two's complement of x.

I have ran the following program to know it
public class Negative {
public static void main(String[] args) {
int i =10;
int j = -10;
System.out.println(Integer.toBinaryString(i));
System.out.println(Integer.toBinaryString(j));
}
}
Output is
1010
11111111111111111111111111110110
From the output it seems that it has been using two's complement.

Oracle provides some documentation regarding Java Datatypes that you may find interesting. Specifically:
int: The int data type is a 32-bit signed two's complement integer. It has a minimum value of -2,147,483,648 and a maximum value of 2,147,483,647 (inclusive).
Btw, short is also stored as two's complement.

Positive numbers are stored/retrived as it is.
e.g) For +ve number 10; byte representation will be like 0-000 0010
(0 - MSB will represent that it is +ve).
So while retrieving based on MSB; it says it is +ve,
so the value will be taken as it is.
But negative numbers will be stored after 2's complement (other than
MSB bit), and MSB bit will be set to 1.
e.g) when storing -10 then
0-000 0010 -> (1's complement) -> 0-111 1101
-> (2's complement) 0-111 1101 + 1 -> 0-111 1110
Now MSB will be set to one, since it is negative no -> 1-111 1110
when retrieving, it found that MSB is set to 1. So it is negative no.
And 2's complement will be performed other than MSB.
1-111 1110 --> 1-000 0001 + 1 --> 1-000 0010
Since MSB representing this is negative 10 --> hence -10 will be retrived.
Casting
Also note that when you are casting int/short to byte, only last byte will be considered along with last byte MSB,
Take example "-130" short, it might be stored like below
(MSB)1-(2's complement of)130(1000 0010) --> 1-111 1111 0111 1110
Now byte casting took last byte which is 0111 1110. (0-MSB)
Since MSB says it is +ve value, so it will be taken as it is.
Which is 126. (+ve).
Take another example "130" short, it might be stored like below
0-000 000 1000 0010 (MSB = 0)
Now byte casting took last byte which is 1000 0010 . (1=MSB)
Since MSB says it is -ve value, 2's complement will be performed and negative number will be returned. So in this case -126 will be returned.
1-000 0010 -> (1's complement) -> 1-111 1101
-> (2's complement) 1-111 1101 + 1 -> 1-111 1110 -> (-)111 1110
= -126
Diff between (int)(char)(byte) -1 AND (int)(short)(byte) -1
(byte)-1 -> 0-000 0001 (2's Comp) -> 0-111 1111 (add sign) -> 1-111 1111
(char)(byte)-1 -> 1-111 1111 1111 1111 (sign bit is carry forwarded on left)
similarly
(short)(byte)-1-> 1-111 1111 1111 1111 (sign bit is carry forwarded on left)
But
(int)(char)(byte)-1 -> 0-0000000 00000000 11111111 11111111 = 65535
since char is unsigned; MSB won't be carry forwarded.
AND
(int)(Short)(byte)-1 -> 1-1111111 11111111 11111111 11111111 = -1
since short is signed; MSB is be carry forwarded.
References
Why is two's complement used to represent negative numbers?
What is “2's Complement”?

The most significant bit (32nd) indicates that the number is positive or negative. If it is 0, it means the number is positive and it is stored in its actual binary representation. but if it is 1, it means the number is negative and is stored in its two's complement representation. So when we give weight -2^32 to the 32nd bit while restoring the integer value from its binary representation, We get the actual answer.

According to this document, all integers are signed and stored in two's complement format for java. Not certain of its reliability..

positive numbers are stored directly as binary. 2's compliment is required for negative numbers.
for example:
15 : 00000000 00000000 00000000 00001111
-15: 11111111 11111111 11111111 11110001
here is the difference in signed bit.

Thank you, dreamcrash for the answer https://stackoverflow.com/a/13422442/1065835; on the wiki page they give an example which helped me understand how to find out the binary representation of the negative counterpart of a positive number.
For example, using 1 byte (= 2 nibbles = 8 bits), the decimal number 5
is represented by
0000 01012 The most significant bit is 0, so the pattern represents a
non-negative value. To convert to −5 in two's-complement notation, the
bits are inverted; 0 becomes 1, and 1 becomes 0:
1111 1010 At this point, the numeral is the ones' complement of the
decimal value −5. To obtain the two's complement, 1 is added to the
result, giving:
1111 1011 The result is a signed binary number representing the
decimal value −5 in two's-complement form. The most significant bit is
1, so the value represented is negative.

For positive integer 2'complement value is same with MSB bit 0 (like +14 2'complement is 01110).
For only negative integer only we are calculating 2'complement value (-14= 10001+1 = 10010).
So final answer is both the values(+ve and -ve) are stored in 2'complement form only.

Java - Bitwise comparisons and shifting of bits

I need a little explanation of the following statement, What is it doing?:
int result = 154 + (153 << 8) + (25 << 16) + (64 << 24);
/* what would be the value of result after this line and how it is calculated
Why we need this? */

(153 << 8) is equivalent to 153 * pow(2, 8)
You are actually shifting your bits towards left..
Also: -
(153 >> 8) is equivalent to 153 / pow(2, 8)
You can guess why.. This is actually shifting bits towards right..
E.G: -
3 => 0011
3 << 2 is equal to 1100 -> (Which is code for 12)
3 >> 2 is equal to 0000 -> (Which is code for 0) -> you can see - **(3 / 4 = 0)**
NOTE :- Note that the right shifting rounds off towards negative infinity..
For E.G: -
-3 >> 1 --> -2 (-1.5 is rounded to -2)
Lets see how it happens: -
In binary string representation: -
-3 ==> 11111111111111111111111111111101
-3 >> 1 ==> 11111111111111111111111111111110 (-3 / 2 = -1.5 -> rounded to -2)
(Note the left most bit is filled by the bit that was present at the left most end before shift (1 in this case))
So, the value becomes, -2 (for -3>>1, which is greater than -3)
This happens for negative numbers.. Right shifting a negative number gives a number greater than the original number..
Which is contrary to the positive number where the left most bit will be filled by 0... Thus value obtained will be less than the original..
3 ==> 00000000000000000000000000000011
3 >> 1 ==> 00000000000000000000000000000001 (3 / 2 = 1.5 -> rounded to 1)
(So left most bit remains 0. So, the value is 1 (less than 3), i.e., value is rounded off towards negative infinity and becomes 1 from 1.5)
Similarly you can devise results for left-shifting positive and negative number..

The answer is 1075419546. The left shift operator is basically addings 0s to the binary representations of the decimal numbers so this would simply to
154 + 153 * 2^8 + 25 * 2^16 + 64*2^24
So you can convert 153 to its binary representation, then add 8 zeros and convert back to decimal etc etc..

in practical terms, if you use the given operator on a math expression it has the same meaning as the following:
123 << n is exactly the same as 123 * 2 ^ n
For example, 2 << 2 is 2 * 2 ^ 2 which is 8 or the same as 1000
Otherwise, you are just shifting bits to the left:
3 = 11 then 3 << 2 = 1100.
Hope it makes it clear.

Why if (n & -n) == n then n is a power of 2?

Line 294 of java.util.Random source says
if ((n & -n) == n) // i.e., n is a power of 2
// rest of the code
Why is this?

Because in 2's complement, -n is ~n+1.
If n is a power of 2, then it only has one bit set. So ~n has all the bits set except that one. Add 1, and you set the special bit again, ensuring that n & (that thing) is equal to n.
The converse is also true because 0 and negative numbers were ruled out by the previous line in that Java source. If n has more than one bit set, then one of those is the highest such bit. This bit will not be set by the +1 because there's a lower clear bit to "absorb" it:
n: 00001001000
~n: 11110110111
-n: 11110111000 // the first 0 bit "absorbed" the +1
^
|
(n & -n) fails to equal n at this bit.

The description is not entirely accurate because (0 & -0) == 0 but 0 is not a power of two. A better way to say it is
((n & -n) == n) when n is a power of two, or the negative of a power of two, or zero.
If n is a power of two, then n in binary is a single 1 followed by zeros.
-n in two's complement is the inverse + 1 so the bits lines up thus
n 0000100...000
-n 1111100...000
n & -n 0000100...000
To see why this work, consider two's complement as inverse + 1, -n == ~n + 1
n 0000100...000
inverse n 1111011...111
+ 1
two's comp 1111100...000
since you carry the one all the way through when adding one to get the two's complement.
If n were anything other than a power of two† then the result would be missing a bit because the two's complement would not have the highest bit set due to that carry.
† - or zero or a negative of a power of two ... as explained at the top.

You need to look at the values as bitmaps to see why this is true:
1 & 1 = 1
1 & 0 = 0
0 & 1 = 0
0 & 0 = 0
So only if both fields are 1 will a 1 come out.
Now -n does a 2's complement. It changes all the 0 to 1 and it adds 1.
7 = 00000111
-1 = NEG(7) + 1 = 11111000 + 1 = 11111001
However
8 = 00001000
-8 = 11110111 + 1 = 11111000
00001000 (8)
11111000 (-8)
--------- &
00001000 = 8.
Only for powers of 2 will (n & -n) be n.
This is because a power of 2 is represented as a single set bit in a long sea of zero's.
The negation will yield the exact opposite, a single zero (in the spot where the 1 used to be) in a sea of 1's. Adding 1 will shift the lower ones into the space where the zero is.
And The bitwise and (&) will filter out the 1 again.

In two's complement representation, the unique thing about powers of two, is that they consist of all 0 bits, except for the kth bit, where n = 2^k:
base 2 base 10
000001 = 1
000010 = 2
000100 = 4
...
To get a negative value in two's complement, you flip all the bits and add one. For powers of two, that means you get a bunch of 1s on the left up to and including the 1 bit that was in the positive value, and then a bunch of 0s on the right:
n base 2 ~n ~n+1 (-n) n&-n
1 000001 111110 111111 000001
2 000010 111101 111110 000010
4 000100 111011 111100 000100
8 001000 110111 111000 001000
You can easily see that the result of column 2 & 4 is going to be the same as column 2.
If you look at the other values missing from this chart, you can see why this doesn't hold for anything but the powers of two:
n base 2 ~n ~n+1 (-n) n&-n
1 000001 111110 111111 000001
2 000010 111101 111110 000010
3 000011 111100 111101 000001
4 000100 111011 111100 000100
5 000101 111010 111011 000001
6 000110 111001 111010 000010
7 000111 111000 111001 000001
8 001000 110111 111000 001000
n&-n will (for n > 0) only ever have 1 bit set, and that bit will be the least significant set bit in n. For all numbers that are powers of two, the least significant set bit is the only set bit. For all other numbers, there is more than one bit set, of which only the least significant will be set in the result.

It's property of powers of 2 and their two's complement.
For example, take 8:
8 = 0b00001000
-8 = 0b11111000
Calculating the two's complement:
Starting: 0b00001000
Flip bits: 0b11110111 (one's complement)
Add one: 0b11111000
AND 8 : 0b00001000
For powers of 2, only one bit will be set so adding will cause the nth bit of 2n to be set (the one keeps carrying to the nth bit). Then when you AND the two numbers, you get the original back.
For numbers that aren't powers of 2, other bits will not get flipped so the AND doesn't yield the original number.

Simply, if n is a power of 2 that means only one bit is set to 1 and the others are 0's:
00000...00001 = 2 ^ 0
00000...00010 = 2 ^ 1
00000...00100 = 2 ^ 2
00000...01000 = 2 ^ 3
00000...10000 = 2 ^ 4
and so on ...
and because -n is a 2's complement of n (that means the only bit which is 1 remains as it is and the bits on left side of that bit are sit to 1 which is actually doesn't matter since the result of AND operator & will be 0 if one of the two bits is zero):
000000...000010000...00000 <<< n
&
111111...111110000...00000 <<< -n
--------------------------
000000...000010000...00000 <<< n

Shown through example:
8 in hex = 0x000008
-8 in hex = 0xFFFFF8
8 & -8 = 0x000008