We Keep Coding

I have the method below that gets a two-dimensional array and a value. The method check if the value be in the array or not

I have the method below that gets a two-dimensional array and a value. The method check if the value be in the array or not.
I don't understand why do I need the line of code that I highlighted in bold (if (m[i][m[i].length-1] <= val).
It Looks that the code works without this line as well... Why do I still need this line, can someone explain me please? thanks
public static boolean findValWhat (int[][] m, int val)
{
for (int i = 0; i < m.length; i++) {
**if (m[i][m[i].length-1] <= val){**
if (binarySearch(m[i], val) == val){
return true;
}
}
}
return false;
}

The code will still work without it but is makeing it run faster.
Lets say you have this sorted 2d array:
[[1,2,3],[4,5,6],[7,8,9]]
Then you can see that if you are searching for 8 you don't need to do binary search for the first line because 3 is smaller then 8 and he is the biggest number in there.
You can even make this code batter by doing binary search instead of the loop.

Binary Search using Recursion in java

I am writing a program for a recursive binary search. I have an input file with a series of sorted numbers, which I added to an ArrayList. The program searches to see if a key given by user input is in the ArrayList.
public static int binarySearch(int key, int median){
if(key == (int)array.get(median)){
return key;
}else if(key < (int)array.get(median)){
binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
binarySearch(key,median+1);
}
return -1;
}
For example, let's say the key is 90. I debugged and placed watches at key and array.get(median). After stepping through the program, I discovered that even when key and array.get(median) are equal to 90, the program continues through the loop without ever returning the key. I know that recursion isn't ideal for this, but it's what I need to use.

This does not look like a correct binary search, as a binary search uses a divide and conquer approach. You only divide your list initially once and then check every element from there on. It would be better to then just divide your list again and so on, see https://en.wikipedia.org/wiki/Binary_search_algorithm
Anyway, to get your code running, why you do not get an result is most likely because you do not return the result of the recursion, but instead -1.
Remove the return -1 and set a return before your recursive binarySearch calls. And you are missing a exit condition when you do not find the element.
Example (still not a correct binary search):
public static int binarySearch(int key, int median){
if (median < 0 || median > array.size() - 1) { // element not found
return -1;
}
if (key == (int)array.get(median)){
return key;
} else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
} else{
return binarySearch(key,median+1);
}
}

If all you care about is whether it is in the data structure...
public static boolean binarySearch(int key, int median){
if(key == (int)array.get(median)){
return true;
}else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
return binarySearch(key,median+1);
}
}
your code could be better written, but copied to to get across the important part of it

You should change your code like this:
public static int binarySearch(int key, int median){
if(key == (int)array.get(median)){
return key;
}else if(key < (int)array.get(median)){
return binarySearch(key,median-1);
}else if(key > (int)array.get(median)){
return binarySearch(key,median+1);
}
return -1;
}
If you do this your recursion would end but I will leave it to you to test out your binary search code. There are some things like the start index and the end index that you are ignoring in this method The return statements should be added because if you don't the control moves to the next statement in the method which is undesirable. Hope that helps!

The code posted is not a Binary Search and is, in fact, a Linear Search using recursion. A Binary Search divides the search space in half each step, binary meaning "two halves" in context. The result is that this Linear Search runs in O(n) and not the expected O(lg n) bounds of a Binary Search
Problems/issues (other than it not being a Binary Search):
The values from the recursive cases are lost as they are not themselves returned. The result of a recursive case must be used in some way (or why call the function at all?). In this case the value should be returned directly, eg. return binarySearch(..). This causes "continues through the loop without ever returning the key" - it actually does find the key, but discards the recursive result.
The code does not correctly detect the out-of-bounds terminal condition. This may result in an IndexOutOfBoundsException when the key is not found.
The step-left/right approach might never terminate correctly without further logic. For example, when the list is {1,3,5,7} and the value being sought is 4 the original code will ping-pong between indices 1 (value 3) and 2 (value 4). This will result in a StackOverflowError being thrown.
The key is returned. This makes little sense as the key is already known and it also prevents -1 from being detectable. Return the index found instead, or a boolean if only an existence test is required.
Take some time to understand and fix these issues .. and then read on for a spoiler if needed.
Consider this rewrite fixing the issues outlined above. Note that it is overly complex1 while still employing an inferior algorithm and O(n) performance. In any case;
// By taking in the List we make this function universal and not
// dependent upon a static field. It should probably take in a List<Integer>
// but I don't know what the actual type of "array" is. A more advanced
// implementation would take in List<Comparable> and then be modified to work
// with any objects that correctly implement said interface.
public static int linearSearch(int key, List list, int index, int step) {
if (index < 0 || index >= list.size()) {
// Base case: not found, out of bounds
return -1;
}
int x = (int)list.get(index);
if (key < x && step <= 0) { // need to look left, NOT looking right
// Recursive case: look left, returning result
return linearSearch(key, list, index - 1, -1);
} else if (key > x && step >= 0){ // need to look right, NOT looking left
// Recursive case: look right, returning result
return linearSearch(key, list, index + 1, +1);
} else if (key == x) {
// Base case: found key, return index found
return index;
} else {
// Base case: key not equal, refusing to ping-pong
return -1;
}
}
And then consider the use of this helper/wrapper function;
// Returns the index in "array" where key was found, or -1 if it was not found
public static int linearSearch(int key) {
// Have to start somewhere, might as well be the middle..
// ..but it does NOT make the time complexity any better
// ..and it is still NOT a Binary Search.
return linearSearch(key, array, array.size() / 2, 0);
}
1 Alternatively, since it is a Linear Search it could be rewritten without the extra left/right movement and have the same complexity bounds. (It is also trivial to modify this simpler code to a recursive Binary Search.)
public static int linearSearch(int key, List list, int index) {
if (index >= list.size() {
// Base case: end of list
return -1;
}
int x = (int)list.get(index);
if (key < x) {
// Recursive case: not there yet, keep looking
return linearSearch(key, list, index + 1);
} else if (key == x) {
// Base case: found key, return index
return index;
} else { // -> key > x
// Base case: read past where the key would be found
return -1;
}
}

Here's binary search for ArrayList<Integer> :)
public int binarySearch(List<Integer> list, int find) {
int mid = list.size() / 2;
int val = list.get(mid);
if (val == find) {
return val;
} else if (list.size() == 1) {
return -1;
}
return val > find ?
binarySearch(list.subList(0, mid), find) :
binarySearch(list.subList(mid, list.size()), find);
}

Understanding basic recursion function in Java to calculate positive integers in array

I am trying to learn recursion in Java and have an array that takes in continuous input until the Scanner reads in a 0.
From there I have a method that (attempts) to calculate the number of positive integers in the array using recursion. This is the first recursive function I have ever written and I keep getting a stackoverflow error.
I have read tutorials and I still can't wrap my head around the basic understanding of recursion.
public class reuncF {
private static int start = 0;
private static int end = 98;
public static void main(String[] args) {
input = input.nextDouble();
list[i] = numInput;
computeSumPositive(numList, count);
}
}
return positives += solve(numbers, count++);
}
}

You forgot to stop your recursion!
There has to be some case where computeSumPositive returns without calling itself again. Otherwise it'll just keep going forever, never getting back to you.
If you did it with a loop, the loop would look like this:
int positives = 0;
for (int i = 0; i < numList.length; ++i) {
if (numList[i] > 0) {
positives++;
}
}
To do that recursively, you just find out what are the variables used in the loop. They are i, numList and positives.
computeSumPositive(int i, double[] numList, int positives)
Then we take a look at what the loop does. First, it checks whether we went too far,
so our recursive function should do that too. It'll have to return instead of just falling through like the loop does. And obviously, it must return the result:
{
if (! (i < numList.length))
return positives;
The loop then does the test and maybe increments positives, so the recursive function should also do that:
if (numList[i] > 0) {
positives++;
}
At the end of the loop, i is updated:
i++;
The loop just starts over, but the recursive function will have to call itself. Of course, we want it to use the new value of i and positives, but fortunately we updated those, so now we can just do:
return computeSumPositives (i, numList, positives);
}
The tricky bit is that the values i, numList, and are local to each call. Each invocation of computeSumPositives can see only the arguments it were given. If it changes them, none of the other invocation can see that change.
EDIT: So if we, for reasons we can only speculate about, wanted desperately for computeSumPositive to take only 2 parameters, we would have to "split up" positives across each invocation. Each invocation knows whether or not its number was positive or not; all we have to do is add them. Then it looks like this:
computeSumPositive(int i, double[] numList)
{
if (! (i < numList.length))
return 0; // I didn't find any at index i
if (numList[i] > 0) {
// Theres one I found + however many my later
// invocations will find.
return 1 + computeSumPositive (i+1, numList);
} else {
// I didn't find any, but my later invocations might.
return computeSumPositive (i+1, numList);
}
}

I find it helpful, when dealing with recursion, to figure out the termination case first.
It looks like you are treating 'count' as an index. So you could check if your at the last index in the array, if so and if the value is positive return a 1, if the value is non-positive return a 0 - dont recurse anymore.
If your not at the last index, and the value is positive return a 1 + the recursive function call, or if the value is non-positive just continue to recurse.
This will still cause a stack overflow for large arrays.

The value of count++ is the same as the value of count; the program uses the value and then increments it. But the result is that computeSumPositive keeps calling itself with the same value of count, which leads to infinite recursion. Note that each time computeSumPositive calls another computeSumPositive, each call has its own copy of the parameters (like count) and the local variables; so incrementing one computeSumPositive's copy of count has no effect on the value of count used by other recursive calls.
Change count++ to count + 1, and also add a way to halt the recursion. (At some point, you will be calling computeSumPositive to look at zero integers, and at that point, it should just return 0 and not call itself. You need to think about: how do you test whether you've reached that point?)

Whats wrong with my syntax and am i doing this efficiently?

I'm trying to make a method that will tell me weather or not it is true or false that a number is prime. here's the code:
class prime
{
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
prime (a, b-1) ;
}
else
{
return true;
}
}
public static void main (String[] arg)
{
System.out.println (prime (45, 45)) ;
}
}
when i try to compile this i get this error message:
prime.java:23: missing return statement
}
^
1 error
I could be misinterpreting what the error message is saying but it seems to me that there isn't a missing return statement since i have a return statement for every possible set of conditions. if a is 0 then it returns false, if it isn't then it checks to see if a is dividable by b if it is then it returns if not then if b is greater than 1 it starts over again. if b isn't greater than 1 it also returns.
Also it seems a bit messy to have to
make this method take two ints that
are the same int.
What is wrong with my syntax/ why am i getting the error message? Is there a way to make it so that the method that i use in main only has to take one int (perhaps another method splits that int into two clones that are then passed to public static boolean primeproper?
or is there a more effective way of
going about this that i'm missing
entirely?

In your prime function, there are four possible code paths, one of which doesn't return anything. That is what the error message is complaining about. You need to replace:
prime (a, b-1) ;
with:
return prime (a, b-1) ;
in the else if (b>1) case.
Having said that, this is actually not a good way to calculate if a number is prime. The problem is that every recursive call allocates a stack frame and you'll get into serious stack overflow problems if you're trying to work out whether 99,999,999 is a prime number?
Recursion is a very nice tool for a certain subset of problems but you need to be aware of the stack depth. As to more efficient solutions, the are many tests you can carry out to determine a number is not prime, then only check the others with a brute force test.
One thing you should be aware of is to check divisibility against smaller numbers first since this will reduce your search scope quicker. And don't use divide where multiply will do, multiplication is typically faster (though not always).
And some possibly sneaky tricks along the lines of:
every number other than 2 that ends in 2, 4, 6, 8 or 0 is non-prime.
every number other than 5 that ends in 5 is non-prime.
Those two rules alone will reduce your search space by 60%. Assuming you get your test number as a string, it's a simple matter to test the last digit of that string even before converting to an integral type.
There are some more complex rules for divisibility checks. If you take a multiple of 9 and sum all the digits to get a new number, then do it again to that number, then keep going until you have a single digit, you'll find that it's always 9.
That will give you another 10% reduction in search space albeit with a more time-expensive check. Keep in mind that these checks are only advantageous for really large numbers. The advantages are not so great for, say, 32-bit integers since a pre-calculated bitmap would be much more efficient there (see below).
For a simplistic start, I would use the following iterative solution:
public static boolean prime (int num) {
int t = 2;
while (t * t <= num) {
if ((num % t) == 0) {
return false;
}
t++;
}
return true;
}
If you want real speed in your code, don't calculate it each time at all. Calculate it once to create a bit array (one of the sieve methods will do it) of all primes across the range you're interested in, then simply check your values against that bit array.
If you don't even want the cost of calculating the array every time your program starts, do it once and save the bit array to a disk file, loading it as your program starts.
I actually have a list of the first 100 million primes in a file and it's easier and faster for me to use grep to find if a number is prime, than to run some code to calculate it :-)
As to why your algorithm (fixed with a return statement) insists that 7 is not prime, it will insist that every number is non-prime (haven't checked with negative numbers, I'm pretty sure they would cause some serious problems - your first check should probably be if (a < 1) ...).
Let's examine what happens when you call prime(3,3).
First time through, it hits the third condition so calls prime(3,2).
Then it hits the second condition since 3 % (2-1) == 0 is true (N % 1 is always 0).
So it returns false. This could probably be fixed by changing the third condition to else if (b>2) although I haven't tested that thoroughly since I don't think a recursive solution is a good idea anyway.
The following complete code snippet will do what you need although I appreciate your curiosity in wanting to know what you did wrong. That's the mark of someone who's actually going to end up a good code cutter.
public class prime
{
public static boolean isPrime (int num) {
int t = 2;
while (t * t <= num) {
if ((num % t) == 0) {
return false;
}
t++;
}
return true;
}
public static void main (String[] arg)
{
System.out.println (isPrime (7)) ;
}
}

You seem to be under the impression that because the recursion will eventually find a base-case which will hit a return statement, then that return will bubble up through all of the recursive calls. That's not true. Each recursive call must pass out the result like this:
return prime(a, b - 1);

If b is larger than 1, your function won't return anything.
May it be return prime (a, b-1) ; ?

To improve efficiency, think more about your conditions. Do you really need test every factor from 2 to N? Is there a different stopping point that will help tests of prime numbers complete more quickly?
To make a better API, consider making the recursive method private, with a public entry point that helps bootstrap the process. For example:
public static boolean prime(int n) {
return recurse(n, n);
}
private static boolean recurse(int a, int b) {
...
}
Making a method private means that it can't be called from another class. It's effectively invisible to users of the class. The intent here is to hide the "ugly" extra parameter by providing a public helper method.
Think about the factors of some composite numbers. 10 factors to 5×2. 12 factors to 6×2. 14 factors to 7×2. Now think about 25. 25 factors to 5×5. What about 9? Do you see a pattern? By the way, if this isn't homework, please let me know. Being this didactic is hard on me.

In answer to why 7 isn't working, pretend you're the computer and work through your logic. Here's what you wrote.
class prime
{
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
// Have to add the return statement
// here as others have pointed out!
return prime(a, b-1);
}
else
{
return true;
}
}
public static void main (String[] arg)
{
System.out.println (prime (45, 45)) ;
}
}
So let's start with 7.
if(7 == 0) // not true, don't enter this block
else if(7 % 6 == 0) // not true
else if(7 > 1) // true, call prime(7, 6)
if(7 == 0) // not true, don't enter this block
else if(7 % 5 == 0) // not true
else if(6 > 1) // true, call prime(7, 5)
if(7 == 0) // not true, don't enter this block
else if(7 % 4 == 0) // not true
else if(5 > 1) // true, call prime(7, 4)
... keep going down to calling prime(7, 2)
if(7 == 0) // not true, don't enter this block
else if(7 % 1 == 0) true, return false
When you get down to calling prime(n, 2), it will always return false because you have a logic error.

Your recursive method must return a value so it can unroll.
public static boolean prime (int a, int b)
{
if (a == 0)
{
return false;
}
else if (a%(b-1) == 0)
{
return false;
}
else if (b>1)
{
return prime (a, b-1) ;
}
else
{
return true;
}
}
I might write it a different way, but that is the reason that you are not able to compile the code.

I think the original question was answered already - you need to insert return in the body of else if (b>1) - I just wanted to point out that your code still will crash when given 1 as the value for b, throwing an ArithmeticException since a%(b-1) will be evaluated to a%0, causing a division by zero.
You can avoid this by making the first if-statement if (a == 0 || b == 1) {}
This won't improve the way the program finds primes, it just makes sure there is one less way to crash it.

Similar to #paxdiblo's answer, but slightly more efficient.
public static boolean isPrime(int num) {
if (num <= 1 || (num & 1) == 0) return false;
for (int t = 3; t * t <= num; t += 2)
if (num % t == 0)
return false;
return true;
}
Once it is determined that the number is not even, all the even numbers can be skipped. This will halve the numbers which need to be checked.

How to detect an infinite loop in a recursive call?

I have a function that is recursively calling itself, and i want to detect and terminate if goes into an infinite loop, i.e - getting called for the same problem again. What is the easiest way to do that?
EDIT: This is the function, and it will get called recursively with different values of x and y. i want to terminate if in a recursive call, the value of the pair (x,y) is repeated.
int fromPos(int [] arr, int x, int y)

One way is to pass a depth variable from one call to the next, incrementing it each time your function calls itself. Check that depth doesn't grow larger than some particular threshold. Example:
int fromPos(int [] arr, int x, int y)
{
return fromPos(arr, x, y, 0);
}
int fromPos(int [] arr, int x, int y, int depth)
{
assert(depth < 10000);
// Do stuff
if (condition)
return fromPos(arr, x+1, y+1, depth + 1);
else
return 0;
}

If the function is purely functional, i.e. it has no state or side effects, then you could keep a Set of the arguments (edit: seeing your edit, you would keep a Set of pairs of (x,y) ) that it has been called with, and every time just check if the current argument is in the set. That way, you can detect a cycle if you run into it pretty quickly. But if the argument space is big and it takes a long time to get to a repeat, you may run out of your memory before you detect a cycle. In general, of course, you can't do it because this is the halting problem.

You will need to find a work-around, because as you've asked it, there is no general solution. See the Halting problem for more info.

An easy way would be to implement one of the following:
Pass the previous value and the new value to the recursive call and make your first step a check to see if they're the same - this is possibly your recursive case.
Pass a variable to indicate the number of times the function has been called, and arbitrarily limit the number of times it can be called.

You can only detect the most trivial ones using program analysis. The best you can do is to add guards in your particular circumstance and pass a depth level context. It is nearly impossible to detect the general case and differentiate legitimate use of recursive algorithms.

You can either use overloading for a consistent signature (this is the better method), or you can use a static variable:
int someFunc(int foo)
{
static recursionDepth = 0;
recursionDepth++;
if (recursionDepth > 10000)
{
recurisonDepth = 0;
return -1;
}
if (foo < 1000)
someFunc(foo + 3);
recursionDepth = 0;
return foo;
}
John Kugelman's answer with overloading is better beacuse it's thread safe, while static variables are not.
Billy3

Looks like you might be working on a 2D array. If you've got an extra bit to spare in the values of the array, you can use it as a flag. Check it, and terminate the recursion if the flag has been set. Then set it before continuing on.
If you don't have a bit to spare in the values, you can always make it an array of objects instead.

If you want to keep your method signature, you could keep a couple of sets to record old values of x and y.
static Set<Integer> xs;
static Set<Integer> ys;//Initialize this!
static int n=0;//keeps the count function calls.
int fromPos(int [] arr, int x, int y){
int newX= getX(x);
int newY= getY(y);
n++;
if ((!xs.add(Integer.valueOf(newX)) && !ys.add(Integer.valueOf(newY))){
assert(n<threshold); //threshold defined elsewhere.
fromPos(arr,newx,newy);
}
}

IMHO Only loops can go into an infinite loop.
If your method has too many level of recursion the JVM will throw a StackOverflowError. You can trap this error with a try/catch block and do whatever you plan to do when this condition occurs.

A recursive function terminates in case a condition is fulfilled.
Examples:
The result of a function is 0 or is 1
The maximum number of calls is reached
The result is lower/greater than the input value
In your case the condition is ([x0,y0] == [xN,yN]) OR ([x1,y1] == [xN,yN]) OR ([xN-1,yN-1] == [xN,yN])
0, 1, ...N are the indexes of the pairs
Thus you need a container(vector, list, map) to store all previous pairs and compare them to the current pair.

First use mvn findbugs:gui to open a gui which point to the line where this error is present.
I also faced the same problem and I solved it by adding a boolean variable in the loop verification.
Code before ->
for (local = 0; local < heightOfDiv; local = local + 200) { // Line under Error
tileInfo = appender.append(tileInfo).append(local).toString();
while (true) {
try {
tileInfo = appender.append(tileInfo).append(getTheTextOfTheElement(getTheXpathOfTile(incr))).toString();
incr++;
} catch (Exception e) {
incr = 1;
tileInfo = appender.append(tileInfo).append("/n").toString();
}
}
To Solve this problem, I just added a boolean variable and set it to false in the catch block. Check it down
for (local = 0; local < heightOfDiv; local = local + 200) {
tileInfo = appender.append(tileInfo).append(local).toString();
boolean terminationStatus = true;
while (terminationStatus) {
try {
tileInfo = appender.append(tileInfo).append(getTheTextOfTheElement(getTheXpathOfTile(incr))).toString();
incr++;
} catch (Exception e) {
incr = 1;
tileInfo = appender.append(tileInfo).append("/n").toString();
terminationStatus = false;
}
}
This is how i Solved this problem.
Hope this will help. :)