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Java: Bitwise operation for flag checking

I'm trying to check whether or not a number has the second bit flag (ie 0000 0010). My code is as follows:
int flags = Integer.parseInt(fields[1]);
String strflags = Integer.toBinaryString(flags);
flags = Integer.parseInt(strflags);
int secondBitTest = Integer.parseInt("00000010", 2);
if((flags & secondBitTest) == 2) {
System.out.println("YES");
}
However I think I might be doing this wrong, since when I try to input 147 nothing is returned.

You can check if any bit is set using this code that I found here.
if (x & (1<<n) != 0) {
//n-th bit is set
}
else {
//n-th bit is not set
}
x is the number you wish to check, and n is the bit you want to check. The algorithm works by left-shifting the number 1 by n, and AND-ing it with x.

Finding all Logical Combinations of a Set

I am writing to ask if anyone knows how to go about this. I do not need the code, I would just like the logic behind doing this. So I have a set {A,B,C,D,E}. Now I want to find all combinations of and or OR operators amongst the values in the set.
Some examples below.
A and B and C and D and E
A and B and C and D or E
A and B and C or D and E
From what I know there is 2^n-1 possibilities in the case above. So in the specific example above we would have 8 combinations.
In addition to the Above the values in the set can have two possibilities. For simplicities sake lets say A can be True or False. Likewise B,C,D and E. So what we would potentially have is something like the following :
A=True and B=True and C=True and D=True and E=True
A=True and B=True and C=True and D=True and E=False
A=True and B=True and C=True and D=True or E=True
and so on. So taking this into account we would have 2^(2 * n-1) combinations. So in our specific example above again we would have 16 combinations for a set of 4.
Is there an algorithm that already does this? If not would anyone have some logic to implement this in Java
Thanks,

I think you're saying you want to enumerate (perhaps print) all the distinct expressions of the forms you have described, for some set size n. Since each one can be characterized by a set of flags (=True vs =False at positions 1 ... n, and And vs Or at positions 1 ... n - 1), you can represent each expression as an integer, with each flag corresponding to one (binary) bit. If n has a value for which you could hope to explicitly enumerate all the possibilities, such an integer will be well within the range of a Java long. For comfortably being able to enumerate all the possibilities, such an integer will be within the range of a Java int.
One way to proceed, therefore, would be to write a method to decode in-range integers into expressions according to their bit patterns. You can then iterate over all the appropriate integers (i.e. 0 ... (1 << (2 * n)) - 1), and decode each one into the corresponding expression.

If you have to get possible combination of five boolean values, you can do one thing -
Iterate a loop from zero to binary value "11111".
In each iteration you will get a unique combination of 0 and 1.
Convert 1 to true and 0 to false.
I hope below code will be helpful :
import java.util.ArrayList;
public class Test{
public static void main (String[] args)
{
ArrayList<boolean[]> result = new ArrayList<boolean[]>();
int max_num = Integer.parseInt("11111", 2);
for(int i=max_num; i>=0; i--)
{
String val = String.format("%5s", Integer.toBinaryString(i)).replace(' ', '0');
boolean[] arr = new boolean[5];
char[] charArray = val.toCharArray();
for(int j=0; j<charArray.length;j++)
{
if(charArray[j]=='1')
{
arr[j]=true;
}
else
{
arr[j]=false;
}
}
result.add(arr);
arr=null;
val=null;
}
for(int i=0;i<result.size();i++)
{
for(boolean b: result.get(i))
{
System.out.print(b+" ");
}
System.out.println();
}
}
}
To change the variable count :
Replace same count of 1 with "11111". e.g. if variable count is 6, it should be "111111"
Change "%5s" accordingly. e.g. if variable count is 6, it should be "%6s".
Initialize array "arr" with same count.

Number Guessing Game Over Intervals

I have just started my long path to becoming a better coder on CodeChef. People begin with the problems marked 'Easy' and I have done the same.
The Problem
The problem statement defines the following -:
n, where 1 <= n <= 10^9. This is the integer which Johnny is keeping secret.
k, where 1 <= k <= 10^5. For each test case or instance of the game, Johnny provides exactly k hints to Alice.
A hint is of the form op num Yes/No, where -
op is an operator from <, >, =.
num is an integer, again satisfying 1 <= num <= 10^9.
Yes or No are answers to the question: Does the relation n op num hold?
If the answer to the question is correct, Johnny has uttered a truth. Otherwise, he is lying.
Each hint is fed to the program and the program determines whether it is the truth or possibly a lie. My job is to find the minimum possible number of lies.
Now CodeChef's Editorial answer uses the concept of segment trees, which I cannot wrap my head around at all. I was wondering if there is an alternative data structure or method to solve this question, maybe a simpler one, considering it is in the 'Easy' category.
This is what I tried -:
class Solution //Represents a test case.
{
HashSet<SolutionObj> set = new HashSet<SolutionObj>(); //To prevent duplicates.
BigInteger max = new BigInteger("100000000"); //Max range.
BigInteger min = new BigInteger("1"); //Min range.
int lies = 0; //Lies counter.
void addHint(String s)
{
String[] vals = s.split(" ");
set.add(new SolutionObj(vals[0], vals[1], vals[2]));
}
void testHints()
{
for(SolutionObj obj : set)
{
//Given number is not in range. Lie.
if(obj.bg.compareTo(min) == -1 || obj.bg.compareTo(max) == 1)
{
lies++;
continue;
}
if(obj.yesno)
{
if(obj.operator.equals("<"))
{
max = new BigInteger(obj.bg.toString()); //Change max value
}
else if(obj.operator.equals(">"))
{
min = new BigInteger(obj.bg.toString()); //Change min value
}
}
else
{
//Still to think of this portion.
}
}
}
}
class SolutionObj //Represents a single hint.
{
String operator;
BigInteger bg;
boolean yesno;
SolutionObj(String op, String integer, String yesno)
{
operator = op;
bg = new BigInteger(integer);
if(yesno.toLowerCase().equals("yes"))
this.yesno = true;
else
this.yesno = false;
}
#Override
public boolean equals(Object o)
{
if(o instanceof SolutionObj)
{
SolutionObj s = (SolutionObj) o; //Make the cast
if(this.yesno == s.yesno && this.bg.equals(s.bg)
&& this.operator.equals(s.operator))
return true;
}
return false;
}
#Override
public int hashCode()
{
return this.bg.intValue();
}
}
Obviously this partial solution is incorrect, save for the range check that I have done before entering the if(obj.yesno) portion. I was thinking of updating the range according to the hints provided, but that approach has not borne fruit. How should I be approaching this problem, apart from using segment trees?

Consider the following approach, which may be easier to understand. Picture the 1d axis of integers, and place on it the k hints. Every hint can be regarded as '(' or ')' or '=' (greater than, less than or equal, respectively).
Example:
-----(---)-------(--=-----)-----------)
Now, the true value is somewhere on one of the 40 values of this axis, but actually only 8 segments are interesting to check, since anywhere inside a segment the number of true/false hints remains the same.
That means you can scan the hints according to their ordering on the axis, and maintain a counter of the true hints at that point.
In the example above it goes like this:
segment counter
-----------------------
-----( 3
--- 4
)-------( 3
-- 4
= 5 <---maximum
----- 4
)----------- 3
) 2
This algorithm only requires to sort the k hints and then scan them. It's near linear in k (O(k*log k), with no dependance on n), therefore it should have a reasonable running time.
Notes:
1) In practice the hints may have non-distinct positions, so you'll have to handle all hints of the same type on the same position together.
2) If you need to return the minimum set of lies, then you should maintain a set rather than a counter. That shouldn't have an effect on the time complexity if you use a hash set.

Calculate the number of lies if the target number = 1 (store this in a variable lies).
Let target = 1.
Sort and group the statements by their respective values.
Iterate through the statements.
Update target to the current statement group's value. Update lies according to how many of those statements would become either true or false.
Then update target to that value + 1 (Why do this? Consider when you have > 5 and < 7 - 6 may be the best value) and update lies appropriately (skip this step if the next statement group's value is this value).
Return the minimum value for lies.
Running time:
O(k) for the initial calculation.
O(k log k) for the sort.
O(k) for the iteration.
O(k log k) total.

My idea for this problem is similar to how Eyal Schneider view it. Denoting '>' as greater, '<' as less than and '=' as equals, we can sort all the 'hints' by their num and scan through all the interesting points one by one.
For each point, we keep in all the number of '<' and '=' from 0 to that point (in one array called int[]lessAndEqual), number of '>' and '=' from that point onward (in one array called int[]greaterAndEqual). We can easily see that the number of lies in a particular point i is equal to
lessAndEqual[i] + greaterAndEqual[i + 1]
We can easily fill the lessAndEqual and greaterAndEqual arrays by two scan in O(n) and sort all the hints in O(nlogn), which result the time complexity is O(nlogn)
Note: special treatment should be taken for the case when the num in hint is equals. Also notice that the range for num is 10^9, which require us to have some forms of point compression to fit the array into the memory

One-byte bool. Why?

In C++, why does a bool require one byte to store true or false where just one bit is enough for that, like 0 for false and 1 for true? (Why does Java also require one byte?)
Secondly, how much safer is it to use the following?
struct Bool {
bool trueOrFalse : 1;
};
Thirdly, even if it is safe, is the above field technique really going to help? Since I have heard that we save space there, but still compiler generated code to access them is bigger and slower than the code generated to access the primitives.

Why does a bool require one byte to store true or false where just one bit is enough
Because every object in C++ must be individually addressable* (that is, you must be able to have a pointer to it). You cannot address an individual bit (at least not on conventional hardware).
How much safer is it to use the following?
It's "safe", but it doesn't achieve much.
is the above field technique really going to help?
No, for the same reasons as above ;)
but still compiler generated code to access them is bigger and slower than the code generated to access the primitives.
Yes, this is true. On most platforms, this requires accessing the containing byte (or int or whatever), and then performing bit-shifts and bit-mask operations to access the relevant bit.
If you're really concerned about memory usage, you can use a std::bitset in C++ or a BitSet in Java, which pack bits.
* With a few exceptions.

Using a single bit is much slower and much more complicated to allocate. In C/C++ there is no way to get the address of one bit so you wouldn't be able to do &trueOrFalse as a bit.
Java has a BitSet and EnumSet which both use bitmaps. If you have very small number it may not make much difference. e.g. objects have to be atleast byte aligned and in HotSpot are 8 byte aligned (In C++ a new Object can be 8 to 16-byte aligned) This means saving a few bit might not save any space.
In Java at least, Bits are not faster unless they fit in cache better.
public static void main(String... ignored) {
BitSet bits = new BitSet(4000);
byte[] bytes = new byte[4000];
short[] shorts = new short[4000];
int[] ints = new int[4000];
for (int i = 0; i < 100; i++) {
long bitTime = timeFlip(bits) + timeFlip(bits);
long bytesTime = timeFlip(bytes) + timeFlip(bytes);
long shortsTime = timeFlip(shorts) + timeFlip(shorts);
long intsTime = timeFlip(ints) + timeFlip(ints);
System.out.printf("Flip time bits %.1f ns, bytes %.1f, shorts %.1f, ints %.1f%n",
bitTime / 2.0 / bits.size(), bytesTime / 2.0 / bytes.length,
shortsTime / 2.0 / shorts.length, intsTime / 2.0 / ints.length);
}
}
private static long timeFlip(BitSet bits) {
long start = System.nanoTime();
for (int i = 0, len = bits.size(); i < len; i++)
bits.flip(i);
return System.nanoTime() - start;
}
private static long timeFlip(short[] shorts) {
long start = System.nanoTime();
for (int i = 0, len = shorts.length; i < len; i++)
shorts[i] ^= 1;
return System.nanoTime() - start;
}
private static long timeFlip(byte[] bytes) {
long start = System.nanoTime();
for (int i = 0, len = bytes.length; i < len; i++)
bytes[i] ^= 1;
return System.nanoTime() - start;
}
private static long timeFlip(int[] ints) {
long start = System.nanoTime();
for (int i = 0, len = ints.length; i < len; i++)
ints[i] ^= 1;
return System.nanoTime() - start;
}
prints
Flip time bits 5.0 ns, bytes 0.6, shorts 0.6, ints 0.6
for sizes of 40000 and 400K
Flip time bits 6.2 ns, bytes 0.7, shorts 0.8, ints 1.1
for 4M
Flip time bits 4.1 ns, bytes 0.5, shorts 1.0, ints 2.3
and 40M
Flip time bits 6.2 ns, bytes 0.7, shorts 1.1, ints 2.4

If you want to store only one bit of information, there is nothing more compact than a char, which is the smallest addressable memory unit in C/C++. (Depending on the implementation, a bool might have the same size as a char but it is allowed to be bigger.)
A char is guaranteed by the C standard to hold at least 8 bits, however, it can also consist of more. The exact number is available via the CHAR_BIT macro defined in limits.h (in C) or climits (C++). Today, it is most common that CHAR_BIT == 8 but you cannot rely on it (see here). It is guaranteed to be 8, however, on POSIX compliant systems and on Windows.
Though it is not possible to reduce the memory footprint for a single flag, it is of course possible to combine multiple flags. Besides doing all bit operations manually, there are some alternatives:
If you know the number of bits at compile time
bitfields (as in your question). But beware, the ordering of fields is not guaranteed, which may result in portability issues.
std::bitset
If you know the size only at runtime
boost::dynamic_bitset
If you have to deal with large bitvectors, take a look at the BitMagic library. It supports compression and is heavily tuned.
As others have pointed out already, saving a few bits is not always a good idea. Possible drawbacks are:
Less readable code
Reduced execution speed because of the extra extraction code.
For the same reason, increases in code size, which may outweigh the savings in data consumption.
Hidden synchronization issues in multithreaded programs. For example, flipping two different bits by two different threads may result in a race condition. In contrast, it is always safe for two threads to modify two different objects of primitive types (e.g., char).
Typically, it makes sense when you are dealing with huge data because then you will benefit from less pressure on memory and cache.

Why don't you just store the state to a byte? Haven't actually tested the below, but it should give you an idea. You can even utilize a short or an int for 16 or 32 states. I believe I have a working JAVA example as well. I'll post this when I find it.
__int8 state = 0x0;
bool getState(int bit)
{
return (state & (1 << bit)) != 0x0;
}
void setAllOnline(bool online)
{
state = -online;
}
void reverseState(int bit)
{
state ^= (1 << bit);
}
Alright here's the JAVA version. I've stored it to an Int value since. If I remember correctly even using a byte would utilize 4 bytes anyways. And this obviously isn't be utilized as an array.
public class State
{
private int STATE;
public State() {
STATE = 0x0;
}
public State(int previous) {
STATE = previous;
}
/*
* #Usage - Used along side the #setMultiple(int, boolean);
* #Returns the value of a single bit.
*/
public static int valueOf(int bit)
{
return 1 << bit;
}
/*
* #Usage - Used along side the #setMultiple(int, boolean);
* #Returns the value of an array of bits.
*/
public static int valueOf(int... bits)
{
int value = 0x0;
for (int bit : bits)
value |= (1 << bit);
return value;
}
/*
* #Returns the value currently stored or the values of all 32 bits.
*/
public int getValue()
{
return STATE;
}
/*
* #Usage - Turns all bits online or offline.
* #Return - <TRUE> if all states are online. Otherwise <FALSE>.
*/
public boolean setAll(boolean online)
{
STATE = online ? -1 : 0;
return online;
}
/*
* #Usage - sets multiple bits at once to a specific state.
* #Warning - DO NOT SET BITS TO THIS! Use setMultiple(State.valueOf(#), boolean);
* #Return - <TRUE> if states were set to online. Otherwise <FALSE>.
*/
public boolean setMultiple(int value, boolean online)
{
STATE |= value;
if (!online)
STATE ^= value;
return online;
}
/*
* #Usage - sets a single bit to a specific state.
* #Return - <TRUE> if this bit was set to online. Otherwise <FALSE>.
*/
public boolean set(int bit, boolean online)
{
STATE |= (1 << bit);
if(!online)
STATE ^= (1 << bit);
return online;
}
/*
* #return = the new current state of this bit.
* #Usage = Good for situations that are reversed.
*/
public boolean reverse(int bit)
{
return (STATE ^= (1 << bit)) == (1 << bit);
}
/*
* #return = <TRUE> if this bit is online. Otherwise <FALSE>.
*/
public boolean online(int bit)
{
int value = 1 << bit;
return (STATE & value) == value;
}
/*
* #return = a String contains full debug information.
*/
#Override
public String toString()
{
StringBuilder sb = new StringBuilder();
sb.append("TOTAL VALUE: ");
sb.append(STATE);
for (int i = 0; i < 0x20; i++)
{
sb.append("\nState(");
sb.append(i);
sb.append("): ");
sb.append(online(i));
sb.append(", ValueOf: ");
sb.append(State.valueOf(i));
}
return sb.toString();
}
}
Also I should point out that you really shouldn't utilize a special class for this, but to just have the variable stored within the class that'll be most likely utilizing it. If you plan to have 100's or even 1000's of Boolean values consider an array of bytes.
E.g. the below example.
boolean[] states = new boolean[4096];
can be converted into the below.
int[] states = new int[128];
Now you're probably wondering how you'll access index 4095 from a 128 array. So what this is doing is if we simplify it. The 4095 is be shifted 5 bits to the right which is technically the same as divide by 32. So 4095 / 32 = rounded down (127). So we are at index 127 of the array. Then we perform 4095 & 31 which will cast it to a value between 0 and 31. This will only work with powers of two minus 1. E.g. 0,1,3,7,15,31,63,127,255,511,1023, etc...
So now we can access the bit at that position. As you can see this is very very compact and beats having 4096 booleans in a file :) This will also provide a much faster read/write to a binary file. I have no idea what this BitSet stuff is, but it looks like complete garbage and since byte,short,int,long are already in their bit forms technically you might as well use them as is. Then creating some complex class to access the individual bits from memory which is what I could grasp from reading a few posts.
boolean getState(int index)
{
return (states[index >> 5] & 1 << (index & 0x1F)) != 0x0;
}
Further information...
Basically if the above was a bit confusing here's a simplified version of what's happening.
The types "byte", "short", "int", "long" all are data types which have different ranges.
You can view this link: http://msdn.microsoft.com/en-us/library/s3f49ktz(v=vs.80).aspx
To see the data ranges of each.
So a byte is equal to 8 bits. So an int which is 4 bytes will be 32 bits.
Now there isn't any easy way to perform some value to the N power. However thanks to bit shifting we can simulate it somewhat. By performing 1 << N this equates to 1 * 2^N. So if we did 2 << 2^N we'd be doing 2 * 2^N. So to perform powers of two always do "1 << N".
Now we know that a int will have 32 bits so can use each bits so we can just simply index them.
To keep things simple think of the "&" operator as a way to check if a value contains the bits of another value. So let's say we had a value which was 31. To get to 31. we must add the following bits 0 through 4. Which are 1,2,4,8, and 16. These all add up to 31. Now when we performing 31 & 16 this will return 16 because the bit 4 which is 2^4 = 16. Is located in this value. Now let's say we performed 31 & 20 which is checking if bits 2 and 4 are located in this value. This will return 20 since both bits 2 and 4 are located here 2^2 = 4 + 2^4 = 16 = 20. Now let's say we did 31 & 48. This is checking for bits 4 and 5. Well we don't have bit 5 in 31. So this will only return 16. It will not return 0. So when performing multiple checks you must check that it physically equals that value. Instead of checking if it equals 0.
The below will verify if an individual bit is at 0 or 1. 0 being false, and 1 being true.
bool getState(int bit)
{
return (state & (1 << bit)) != 0x0;
}
The below is example of checking two values if they contain those bits. Think of it like each bit is represented as 2^BIT so when we do
I'll quickly go over some of the operators. We've just recently explained the "&" operator slightly. Now for the "|" operator.
When performing the following
int value = 31;
value |= 16;
value |= 16;
value |= 16;
value |= 16;
The value will still be 31. This is because bit 4 or 2^4=16 is already turned on or set to 1. So performing "|" returns that value with that bit turned on. If it's already turned on no changes are made. We utilize "|=" to actually set the variable to that returned value.
Instead of doing -> "value = value | 16;". We just do "value |= 16;".
Now let's look a bit further into how the "&" and "|" can be utilized.
/*
* This contains bits 0,1,2,3,4,8,9 turned on.
*/
const int CHECK = 1 | 2 | 4 | 8 | 16 | 256 | 512;
/*
* This is some value were we add bits 0 through 9, but we skip 0 and 8.
*/
int value = 2 | 4 | 8 | 16 | 32 | 64 | 128 | 512;
So when we perform the below code.
int return_code = value & CHECK;
The return code will be 2 + 4 + 8 + 16 + 512 = 542
So we were checking for 799, but we recieved 542 This is because bits o and 8 are offline we equal 256 + 1 = 257 and 799 - 257 = 542.
The above is great great great way to check if let's say we were making a video game and wanted to check if so and so buttons were pressed if any of them were pressed. We could simply check each of those bits with one check and it would be so many times more efficient than performing a Boolean check on every single state.
Now let's say we have Boolean value which is always reversed.
Normally you'd do something like
bool state = false;
state = !state;
Well this can be done with bits as well utilizing the "^" operator.
Just as we performed "1 << N" to choose the whole value of that bit. We can do the same with the reverse. So just like we showed how "|=" stores the return we will do the same with "^=". So what this does is if that bit is on we turn it off. If it's off we turn it on.
void reverseState(int bit)
{
state ^= (1 << bit);
}
You can even have it return the current state. If you wanted it to return the previous state just swap "!=" to "==". So what this does is performs the reversal then checks the current state.
bool reverseAndGet(int bit)
{
return ((state ^= (1 << bit)) & (1 << bit)) != 0x0;
}
Storing multiple non single bit aka bool values into a int can also be done. Let's say we normally write out our coordinate position like the below.
int posX = 0;
int posY = 0;
int posZ = 0;
Now let's say these never wen't passed 1023. So 0 through 1023 was the maximum distance on all of these. I'm choose 1023 for other purposes as previously mentioned you can manipulate the "&" variable as a way to force a value between 0 and 2^N - 1 values. So let's say your range was 0 through 1023. We can perform "value & 1023" and it'll always be a value between 0 and 1023 without any index parameter checks. Keep in mind as previously mentioned this only works with powers of two minus one. 2^10 = 1024 - 1 = 1023.
E.g. no more if (value >= 0 && value <= 1023).
So 2^10 = 1024, which requires 10 bits in order to hold a number between 0 and 1023.
So 10x3 = 30 which is still less than or equal to 32. Is sufficient for holding all these values in an int.
So we can perform the following. So to see how many bits we used. We do 0 + 10 + 20. The reason I put the 0 there is to show you visually that 2^0 = 1 so # * 1 = #. The reason we need y << 10 is because x uses up 10 bits which is 0 through 1023. So we need to multiple y by 1024 to have unique values for each. Then Z needs to be multiplied by 2^20 which is 1,048,576.
int position = (x << 0) | (y << 10) | (z << 20);
This makes comparisons fast.
We can now do
return this.position == position;
apposed to
return this.x == x && this.y == y && this.z == z;
Now what if we wanted the actual positions of each?
For the x we simply do the following.
int getX()
{
return position & 1023;
}
Then for the y we need to perform a left bit shift then AND it.
int getY()
{
return (position >> 10) & 1023;
}
As you may guess the Z is the same as the Y, but instead of 10 we use 20.
int getZ()
{
return (position >> 20) & 1023;
}
I hope whoever views this will find it worth while information :).

If you really want to use 1 bit, you can use a char to store 8 booleans, and bitshift to get the value of the one you want. I doubt it will be faster, and it's probably going to gives you a lot of headaches working that way, but technically it's possible.
On a side note, an attempt like this could prove useful for systems that don't have a lot of memory available for variables but do have some more processing power then what you need. I highly doubt you will ever need it though.

How to find the closest value of 2^N to a given input?

I somehow have to keep my program running until the output of the exponent function exceeds the input value, and then compare that to the previous output of the exponent function. How would I do something like that, even if in just pseudocode?

Find logarithm to base 2 from given number => x := log (2, input)
Round the value acquired in step 1 both up and down => y := round(x), z := round(x) + 1
Find 2^y, 2^z, compare them both with input and choose the one that suits better

Depending on which language you're using, you can do this easily using bitwise operations. You want either the value with a single 1 bit set greater than the highest one bit set in the input value, or the value with the highest one bit set in the input value.
If you do set all of the bits below the highest set bit to 1, then add one you end up with the next greater power of two. You can right shift this to get the next lower power of two and choose the closer of the two.
unsigned closest_power_of_two(unsigned value)
{
unsigned above = (value - 1); // handle case where input is a power of two
above |= above >> 1; // set all of the bits below the highest bit
above |= above >> 2;
above |= above >> 4;
above |= above >> 8;
above |= above >> 16;
++above; // add one, carrying all the way through
// leaving only one bit set.
unsigned below = above >> 1; // find the next lower power of two.
return (above - value) < (value - below) ? above : below;
}
See Bit Twiddling Hacks for other similar tricks.

Apart from the looping there's also one solution that may be faster depending on how the compiler maps the nlz instruction:
public int nextPowerOfTwo(int val) {
return 1 << (32 - Integer.numberOfLeadingZeros(val - 1));
}
No explicit looping and certainly more efficient than the solutions using Math.pow. Hard to say more without looking what code the compiler generates for numberOfLeadingZeros.
With that we can then easily get the lower power of 2 and then compare which one is nearer - the last part has to be done for each solution it seems to me.

set x to 1.
while x < target, set x = 2 * x
then just return x or x / 2, whichever is closer to the target.

public static int neareastPower2(int in) {
if (in <= 1) {
return 1;
}
int result = 2;
while (in > 3) {
in = in >> 1;
result = result << 1;
}
if (in == 3) {
return result << 1;
} else {
return result;
}
}

I will use 5 as input for an easy example instead of 50.
Convert the input to bits/bytes, in this case 101
Since you are looking for powers of two, your answer will all be of the form 10000...00 (a one with a certain amount of zeros). You take the input value (3 bits) and calculate the integer value of 100 (3 bits) and 1000 (4 bits). The integer 100 will be smaller then the input, the integer 1000 will be larger.
You calculate the difference between the input and the two possible values and use the smallest one. In this case 100 = 4 (difference of 1) while 1000 = 8 (difference of 3), so the searched answer is 4

public static int neareastPower2(int in) {
return (int) Math.pow(2, Math.round(Math.log(in) / Math.log(2)));
}

Here's the pseudo code for a function that takes the input number and returns your answer.
int findit( int x) {
int a = int(log(x)/log(2));
if(x >= 2^a + 2^(a-1))
return 2^(a+1)
else
return 2^a
}

Here's a bitwise solution--it will return the lessor of 2^N and 2^(N+1) in case of a tie. This should be very fast compare to invoking the log() function
let mask = (~0 >> 1) + 1
while ( mask > value )
mask >> 1
return ( mask & value == 0 ) ? mask : mask << 1