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Issues with Binary Search Algorithm

I have an assignment to write a binary search that returns the first iteration of the value we are looking for. I've been doing some research online and my search looks a lot like what i'm finding but i'm having an issue. If I pass this code an array that looks like this {10,5,5,3,2} it find the 5 at in the middle(The first thing it checks) and then just returns it. But that is not the first iteration of the 5 it is the second. What am I doing wrong? Is this even possible?
Thanks in advance!
The code(I'm using Java):
public static int binarySearch(int[] arr, int v){
int lo = 0;
int hi = arr.length-1;
while(lo <= hi){
int middle = (lo+hi)/2;
if(v == arr[middle]){
return middle;
}
else
{
if(v < arr[middle]){
lo = middle+1;
}
else
{
hi = middle-1;
}
}
}
return -1;
}

Here is a modified algorithm that works.
public static int binarySearch(int[] arr, int v) {
int lo = -1;
int hi = arr.length - 1;
while (hi - lo > 1 ) {
int middle = (lo + hi) / 2;
if (arr[middle] > v) {
lo = middle;
} else {
hi = middle;
}
}
if (v == arr[hi]) {
return hi;
} else {
return -1;
}
}
The key points are:
The interval (lo, hi] is exclusive to the left, inclusive to the right.
At each step we throw away one half of the interval. We stop when we are down to one element. Attempts to terminate early offer only a minimal performance boost, while they often affect code legibility and/or introduce bugs.
When arr[middle] = v we assign hi = middle, thus throwing away the right half. This is safe to do because we don't care any occurrences of v past middle. We do care about arr[middle], which may or may not be the first occurrence, and it is for this reason that we made (lo, hi] inclusive to the right. If there are occurrences of v before middle, we will find them in subsequent iterations.
As a side note, the more natural definition [0, n) inclusive to the left, exclusive to the right, can be used to find the last occurrence of v.
In my experience, this inclusive-exclusive interval definition produces the shortest, clearest and most versatile code. People keep trying to improve on it, but they often get tangled up in corner cases.

Having trouble with divide and conquer algorithm for adding consecutive pairs of ints in an array

So I am attempting to get my head around the divide and conquer principle and multiple recursive calls in a single method. It's going ok but I have a problem with the output of the method I am writing.
The purpose of the method is to return the sum of all the pairs of consecutive numbers in an array. I am 95% there but am not getting the output I expect and have been banging me head against the desk for ages trying to work out why.
The array is:
int[] array = { 11, 6, 87, 32, 15, 5, 9, 21 };
and the method is:
public int consecutivePairsSum_DivideAndConquer(int start, int end, int[] array) {
int leftSum;
int rightSum;
int middle = (start + end) / 2;
if (start == middle) {
return array[middle];
} else {
leftSum = array[start] + array[start + 1];
leftSum += consecutivePairsSum_DivideAndConquer(start, middle, array);
}
if (middle == end) {
return array[end];
} else {
rightSum = array[middle] + array[middle+1];
rightSum += consecutivePairsSum_DivideAndConquer(middle+1, end, array);
}
return leftSum + rightSum;
}
Here's my method call:
System.out.println(rF.consecutivePairsSum_DivideAndConquer(0, array.length-1, array));
I think it must be something to do with how I have split the array but no amount of experimenting is giving me the right output.
Expected output: 340
Actual output: 330
Any suggestions most welcome, this is driving me nuts! :p
ps Any useful links to where I can find a solid online tutorial/good book about recursion would also be great (if that's within the scope of SO seeing how it's not direct help with a programming issue)

Here's an outline of the algorithm:
Base case: If your array has less than two elements, the result is 0 (because there are no pairs).
Otherwise: Divide the array into two halves, calculate the results for left and right halves, then the result for the whole array would be <result of left half> + <result of right half> + <last element of left half> + <first element of right half> (Because the only pair missing here is the pair at the location of the split).
In java, it would be something like this:
int consPairSum(int[] array, int left, int right) {
if(right <= left + 1) return 0;
int mid = (left + right) / 2;
int leftPairSum = consPairSum(array, left, mid);
int rightPairSum = consPairSum(array, mid, right);
return leftPairSum + rightPairSum + array[mid - 1] + array[mid];
}
It should be called as
consPairSum(array, 0, array.length);

who said divide and conquer needs to divide into equal chunks you just need to divide into self similar problem. almost 1 liner.
static private int doTheThing(int[] list){
if (list.length==2)
return list[0]+list[1];
return list[0]+list[1]+doTheThing(Arrays.copyOfRange(list,1,list.length));
}

sort array using recursive method

I am working on trying to write a program where a user will enter 6 strings and then it will sort the array in reverse alphabetical order using a recursive method. This is one concept I do not understand despite multiple videos, readings and attempts. Any support and insight is greatly appreciated. Thank you.
import java.util.Arrays;
import java.util.Scanner;
public class SRecusion {
public static void sort2 (String[] sort2) {
int i;
int min = 0;
int max;
for (i = 0; i <sort2.length -1; i++) {
if (sort2[i].charAt(0)> sort2[i=1].charAt(0)) {
sort2[i] = sort2[min];
}
else {
min = (sort2(sort2[i-1]));
}
}
}
public static void main(String[] args) {
// TODO Auto-generated method stub
String [] test = new String[6];
Scanner scnr = new Scanner(System.in);
String userEntry = "";
for(int i = 0; i <= test.length - 1; i++) {
System.out.println("Please enter a word:");
test[i] = scnr.nextLine();
}
sort2(test);
System.out.println("your list is" + Arrays.asList(test));
System.out.println();
}
}

Sorting is a pretty broad topic as there are many different sorting methods (quicksort, merge sort, etc.) However, a pretty basic and simple sorting method is bubble sort. Although it isn't the fastest one, it's pretty easy to understand and code using recursion.
Essentially, bubble sort with iterate through the elements in pairs of 2 and swap the two elements if they're in the wrong order.
For example, let's sort (3, 2, 5, 4, 1) using bubble sort.
(2, 3, 5, 4, 1) First, it'll look at the first two elements swap them if needed. Since 3 is greater than 2, it'll swap them.
(2, 3, 5, 4, 1) Next, it'll look at 3 and 5. Since 3 is less than 5, there is no need to swap
(2, 3, 4, 5, 1) It now looks at 5 and 4 and swaps them.
(2, 3, 4, 1, 5) Finally, it looks at 5 and 1 and swaps them.
Now start from the beginning and repeat the whole process. The sorting ends if exactly 0 swaps are made during an iteration.
If you're still a bit confused, try watching a tutorial on bubble sort or visit this link.

So from what I was asking above as to why you need a recursive sorting algorithm Here it goes I will try to explain how recursive sorting works. It took my some time to figure it out as I am sure it does for most people who first come in contact with it.
public static void Qsort(int[] array, int start, int end)
{
//find the current center of the whole or parital array part I am working on.
int center = (start+end)/2;
///System.out.println("\n This is the center : " + center);
int pivot, i, pivotplace;
i = 0;
pivot = 0;
pivotplace = 0;
//if start = end then we are at a single element. just return to the previous iterative call.
if(start == end)
{
// System.out.println("\n Inside base case return :");
return;
}
//find the pivot value we are using. using a 3 prong selection we are assured to at least get some type of median value and avoid the N^2 worst case.
pivot = getpivot(array[start], array[center], array[end]); //gets median value of start, center and end values in the array.
// System.out.println("\n pivotvalue is : " + pivot);
//find where the current pivot is located and swap it with the last element in the current portion of the array.
if(array[start] == pivot)
{
//System.out.print("\n Inside pivot at start");
swap(array, start, end);
}
else
{
if(array[center] == pivot)
{
//System.out.print("\n Inside pivot at center");
swap(array, center, end);
}
}
//due to iteration the pivot place needs to start at the passed in value of 'start' and not 0.
pivotplace = start;
//due to iteration the loop needs to go from the passed in value of start and not 0 and needs to go
//until it reaches the end value passed in.
for(i = start; i < end; i++)
{
//if the current slot of the array is less than then pivot swap it with the current pivotplace holder
//since the pivotplace keeps getting iterated up be each swap the final place of pivot place
//is where the pivot will actually be swapped back to after the loop cpompletes.
if(array[i] < pivot)
{
//System.out.print("\n Swapping");
swap(array, i, pivotplace);
pivotplace++;
}
}
//loop is finished, swap the pivot into the spot it belongs in.
swap(array, pivotplace, end);
//there are 2 cases for recursive iteration.
//The first is from the start to the slot before the pivot
if(start < pivotplace){Qsort(array, start, pivotplace-1);}
//the second is from the slot after the pivot to the end.
if(pivotplace+1 < end){Qsort(array, pivotplace+1, end);}
}
public static int getpivot(int a, int b, int c)
{
if((a > b) && (a < c))
{
return a;
}
if((b > a) && (b < c))
{
return b;
}
return c;
}
public static void swap(int[] array, int posa, int posb)
{
int temp;
temp = array[posa];
array[posa] = array[posb];
array[posb] = temp;
}
This is a basic Quick Sort or recursive sort I wrote this while in programming classes. You will probably not need to use the getpivot code as you are dealing with a small set of strings, but if you do some research you will see using a possible sample of 3 drastically speeds up the recursion due to balanced work load of the recursion tree.

Sort Array using recursion in kotlin
fun main() {
print(sortArray(arrayListOf(1,3,2,6,8,3)))
}
fun sortArray(arr: MutableList<Int>): MutableList<Int>{
if(arr.size==1) {
return arr
}
val lastValue = arr.last()
arr.removeLast()
sortArray(arr)
insert(arr, lastValue)
return arr
}
fun insert (arr: MutableList<Int>, value: Int): MutableList<Int> {
if(arr.size == 0 || arr.last() < value) {
arr.add(value)
return arr
}
val lastValue = arr.last()
arr.removeLast()
insert(arr, value)
arr.add(lastValue)
return arr
}

Java Quicksort quadratic runtime behaviour

I tried to implement an efficient sorting algorithm in Java. For this reason, I also implemented quicksort and use the following code:
public class Sorting {
private static Random prng;
private static Random getPrng() {
if (prng == null) {
prng = new Random();
}
return prng;
}
public static void sort(int[] array) {
sortInternal(array, 0, array.length - 1);
}
public static void sortInternal(int[] array, int start, int end) {
if (end - start < 50) {
insertionSortInternal(array, start, end);
} else {
quickSortInternal(array, start, end);
}
}
private static void insertionSortInternal(int[] array, int start, int end) {
for (int i=start; i<end - 1; ++i) {
for (int ptr=i; ptr>0 && array[ptr - 1] < array[ptr]; ptr--) {
ArrayUtilities.swap(array, ptr, ptr - 1);
}
}
}
private static void quickSortInternal(int[] array, int start, int end) {
int pivotPos = getPrng().nextInt(end - start);
int pivot = array[start + pivotPos];
ArrayUtilities.swap(array, start + pivotPos, end - 1);
int left = start;
int right = end - 2;
while (left < right) {
while (array[left] <= pivot && left < right) {
++left;
}
if (left == right) break;
while (array[right] >= pivot && left < right) {
right--;
}
if (left == right) break;
ArrayUtilities.swap(array, left, right);
}
ArrayUtilities.swap(array, left, end - 1);
sortInternal(array, start, left);
sortInternal(array, left + 1, end);
}
}
ArrayUtilities.swap just swaps the two given elements in the array. From this code, I expect O(n log(n)) runtime behaviour. But, some different lengths of arrays to sort gave the following results:
10000 elements: 32ms
20000 elements: 128ms
30000 elements: 296ms
The test ran 100 times in each case, and then the arithmetic mean of the running times was calculated. But clearly, as opposed to the expected behaviour, the runtime is O(n^2). What's wrong with my algorithm?

In your insertion-sort implementation your array will be sorted in descending order, while in your quick-sort the array is sorted in ascending order. So replace(for descending order):
for (int ptr=i; ptr>0 && array[ptr - 1] < array[ptr]; ptr--)
with
for (int ptr=i; ptr>0 && array[ptr - 1] > array[ptr]; ptr--)
It also seems like your indexing is not correct.
Try to replace:
sortInternal(array, 0, array.length - 1);
with:
sortInternal(array, 0, array.length);
And in the insertions sort first for loop you don't need to do end - 1, i.e. use:
for (int i=start; i<end; ++i)
Finally, add if (start >= end) return; at the beginning of the quick-sort method.
And as #ljeabmreosn mentioned, 50 is a little bit too large, I would have chosen something between 5 and 20.
Hope that helps!

The QuickSort "optimized" with Insertion Sort for arrays with length less than 50 elements seems to be a problem.
Imagine I had an array of size 65, and the pivot happened to be the median of that array. If I ran the array through your code, your code would use Insertion Sort on the two 32 length subarrays to the left and right of the pivot. This would result in ~O(2*(n/2)^2 + n) = ~O(n^2) average case. Using quick sort and implementing a pivot picking strategy for the first pivot, the time average case would be ~O((nlog(n)) + n) = ~O(n(log(n) + 1)) = ~O(n*log(n)). Don't use Insertion Sort as it is only used when the array is almost sorted. If you are using Insertion Sort solely because of the real running time of sorting small arrays might run faster than the standard quick sort algorithm (deep recursion), you can always utilize a non-recursive quick sort algorithm which runs faster than Insertion Sort.
Maybe change the "50" to "20" and observe the results.

Recursive Partition Sort is Acting Ineffecient

I have written a recursive method for a partition sort that sorts the array however when I use an array of more than 10-20 elements the program takes a really long time to complete (On my computer a bubble sort of a 100,000 int array will take about 15-20 seconds but with an array of only 30 ints my partition sort is taking around 45 seconds to be sorted.
Here is the code.
public static int[] partitionSortRecursive(int[] array, int beginning, int end)
{
if (end < beginning)
return array;
int pivot = (array[beginning] + array[end]) / 2;
int firstUnknown = beginning;
int lastS1 = beginning - 1;
int firstS3 = end + 1;
while (firstUnknown < firstS3)
{
if (array[firstUnknown] == pivot)
{
firstUnknown++;
}
else if (array[firstUnknown] > pivot)
{
firstS3--;
int temp = array[firstUnknown];
array[firstUnknown] = array[firstS3];
array[firstS3] = temp;
}
else
{
lastS1++;
int temp = array[firstUnknown];
array[firstUnknown] = array[lastS1];
array[lastS1] = temp;
firstUnknown++;
}
}
partitionSortRecursive(array, 0, lastS1);
partitionSortRecursive(array, firstS3, end);
return array;
}

You do not use the correct pivot element. You calculate the average of the left and right value but you have to take a sample value from the sub array to partition instead.
You may take the rightmost, the center or any other element. So your first line of codes should look like this
int pivot = array[(beginning + end) / 2];
// or
int pivot = array[end];
You could also take any other element (e.g. random)
EDIT: This does not solve the performance issue.
To my understanding, quick sort will divide an array into two sub arrays A and B where all elements in A are smaller than any element in B and then perform the same operation onto the two sub arrays.
So the basic call structure should be like this
void DoSort (array, i, j)
{
pivot = Partition (array, i, j)
DoSort (array, i,pivot)
DoSort (array, pivot + 1, j)
}
Put your implementation is basically
void DoSort (array, i, j)
{
pivot = Partition (array, i, j)
DoSort (array, 0, pivot) // <<<<<< notice the '0' instead of 'i'
DoSort (array, pivot + 1, j)
}
So you always start from the very beginning of the original array which will most likely take a while

Instead of direct recoursive call like this
partitionSortRecursive(array, 0, lastS1);
partitionSortRecursive(array, firstS3, end);
Organize internal stack where you can save index pairs. While the stack is not empty get the next pair from the stack. In the end of function don't call the same function but put in the stack 2 pairs (0, lastS1) and (firstS3, end)