fixed coding guidelines and added a lot of testcode

MedianOfMedians.h

@@ -4,14 +4,16 @@
 // https://oneraynyday.github.io/algorithms/2016/06/17/Median-Of-Medians/
 // https://www.geeksforgeeks.org/kth-smallestlargest-element-unsorted-array-set-3-worst-case-linear-time/
 
-int findMedian(std::vector<size_t> values) {
+int findMedian(std::vector<size_t> values)
+{
     size_t median;
     size_t size = values.size();
     median = values[(size / 2)];
     return median;
 }
 
-int findMedianOfMedians(std::vector<std::vector<size_t> > values) {
+int findMedianOfMedians(std::vector<std::vector<size_t> > values)
+{
     std::vector<size_t> medians;
     for (size_t i = 0; i < values.size(); i++) {
         size_t m = findMedian(values[i]);
@@ -20,14 +22,16 @@ int findMedianOfMedians(std::vector<std::vector<size_t> > values) {
     return findMedian(medians);
 }
 
-size_t getMedianOfMedians(const std::vector<size_t> values, size_t k) {
+size_t getMedianOfMedians(const std::vector<size_t> values, size_t k)
+{
     // Divide the list into n/5 lists of 5 elements each
     std::vector<std::vector<size_t> > vec2D;
     size_t count = 0;
     while (count != values.size()) {
         size_t countRow = 0;
         std::vector<size_t> row;
-        while ((countRow < 5) && (count < values.size())) {
+        while ((countRow < 5) && (count < values.size()))
+        {
             row.push_back(values[count]);
             count++;
             countRow++;
@@ -41,44 +45,41 @@ size_t getMedianOfMedians(const std::vector<size_t> values, size_t k) {
     // Partition the list into unique elements larger than 'm' (call this sublist L1) and those smaller them 'm' (call this sublist L2)
     std::vector<size_t> L1, L2;
 
-    for (size_t i = 0; i < vec2D.size(); i++) {
+    for (size_t i = 0; i < vec2D.size(); i++)
-        for (size_t j = 0; j < vec2D[i].size(); j++) {
+    {
-            if (vec2D[i][j] > m) {
+        for (size_t j = 0; j < vec2D[i].size(); j++)
+        {
+            if (vec2D[i][j] > m)
+            {
                 L1.push_back(vec2D[i][j]);
             }
-            else if (vec2D[i][j] < m) {
+            else if (vec2D[i][j] < m)
+            {
                 L2.push_back(vec2D[i][j]);
             }
         }
     }
 
-    if (k <= L1.size()) {
+    if (k <= L1.size())
+    {
         return getMedianOfMedians(L1, k);
     }
-    else if (k > (L1.size() + 1)) {
+    else if (k > (L1.size() + 1))
+    {
         return getMedianOfMedians(L2, k - ((int)L1.size()) - 1);
     }
     return m;
 }
 
-// custom swap function
+// A simple function to find median of arr[].
-void swap(size_t* a, size_t* b)
+// This is called only for an array of size 5 in this program.
-{
-    size_t temp = *a;
-    *a = *b;
-    *b = temp;
-}
-
-// A simple function to find median of arr[].  This is called
-// only for an array of size 5 in this program.
 int findMedian(size_t arr[], int n)
 {
     std::sort(arr, arr + n);  // Sort the array
     return arr[n / 2];   // Return middle element
 }
 
-// It searches for x in arr[l..r], and partitions the array
+// searches for x in arr[l..r], and partitions the array around x
-// around x.
 int partition(size_t arr[], int l, int r, int x)
 {
     // Search for x in arr[l..r] and move it to end
@@ -90,12 +91,12 @@ int partition(size_t arr[], int l, int r, int x)
 
     // Standard partition algorithm
     i = l;
-    for (int j = l; j <= r - 1; j++)
+    for (int j = l; j < r; j++)
     {
         if (arr[j] <= x)
         {
-            swap(&arr[i], &arr[j]);
             i++;
+            swap(&arr[i], &arr[j]);
         }
     }
     swap(&arr[i], &arr[r]);

MedianQuicksort.h

@@ -3,13 +3,15 @@
 size_t pivotPartition(std::vector<size_t>& values, size_t left, size_t right) {
     size_t pivotIndex = left + (right - left) / 2;
     size_t pivotValue = values[pivotIndex];
-    size_t i = left;
+    int i = left;
-    size_t j = right;
+    int j = right;
     while (i <= j) {
-        while (values[i] < pivotValue) {
+        while (values[i] < pivotValue)
+        {
             i++;
         }
-        while (values[j] > pivotValue) {
+        while (values[j] > pivotValue)
+        {
             j--;
         }
         if (i <= j) {
@@ -21,7 +23,8 @@ size_t pivotPartition(std::vector<size_t>& values, size_t left, size_t right) {
     return i;
 }
 
-void quicksort(std::vector<size_t>& values, size_t left, size_t right) {
+void quicksort(std::vector<size_t>& values, size_t left, size_t right)
+{
     if (left < right) {
         size_t pivotIndex = pivotPartition(values, left, right);
         quicksort(values, left, pivotIndex - 1);
@@ -29,7 +32,8 @@ void quicksort(std::vector<size_t>& values, size_t left, size_t right) {
     }
 }
 
-size_t getQuicksortMedian(std::vector<size_t> values, size_t i) {
+size_t getQuicksortMedian(std::vector<size_t> values, size_t i)
+{
     //std::qsort(numbers); // only takes array param -> custom implementation with vector
     quicksort(values, 0, values.size() - 1);
     return values[i];

RandomizedSelect.h

@@ -2,42 +2,112 @@
 
 #include <vector>
 
-/*
+// Lomuto Partitioning
-// Pseudo code Alux Nimmervoll, Algo vo3
+int randomizedPartition(std::vector<size_t>& values, int p, int r)
-// Anmerkung: code funktioniert!
+{
+    int i = p + rand() % (r - p); // generate a random number in {p, ..., r}
+    swap(&values[i], &values[r]);
 
-RANDOMIZED-SELECT(A,p,r,i)
+    int pivotValue = values[r];
-    if (p==r) then return A[p]
-    q=RANDOMIZED_PARTITION(A,p,r) //Pivot Element A[q]
-    k=q-p+1 //Anzahl Elemente A[p..q]
-    if (i==k) then return A[q] //Pivot ist das gesuchte
-    elseif (i<k)
-    then return RANDOMIZED-SELECT(A,p,q-1,i)
-    else return RANDOMIZED-SELECT(A,q+1,r,i-k)
-*/
-
-size_t randomizedPartition(std::vector<size_t>& values, size_t p, size_t r) {
-    size_t i = p + rand() % (r - p + 1); // generate a random number in {p, ..., r}
-    std::swap(values[i], values[r]);
-
-    size_t pivotValue = values[r];
     i = p - 1;
-    for (size_t j = p; j < r; j++) {
+    for (int j = p; j < r; j++)
-        if (values[j] <= pivotValue) {
+    {
+        if (values[j] <= pivotValue)
+        {
             i++;
-            std::swap(values[i], values[j]);
+            swap(&values[i], &values[j]);
         }
     }
-    std::swap(values[i + 1], values[r]);
+    swap(&values[i + 1], &values[r]);
-    return i + 1;
+    return (i + 1);
 }
 
-size_t randomizedSelect(std::vector<size_t> values, size_t p, size_t r, size_t i)
+// TODO: Hoare Partitioning
+// https://www.geeksforgeeks.org/quicksort-using-random-pivoting/
+int randomizedPartition2(std::vector<size_t>& values, int low, int high)
 {
+    int i = low + rand() % (high - low); // generate a random number in {p, ..., r}
+    std::swap(values[i], values[low]);
+
+    int pivot = values[low];
+    i = low - 1;
+    int j = high + 1;
+    while (true) {
+        // Find leftmost element greater than
+        // or equal to pivot
+        do {
+            i++;
+        } while (values[i] < pivot);
+
+        // Find rightmost element smaller than
+        // or equal to pivot
+        do {
+            j--;
+        } while (values[j] > pivot);
+
+        // If two pointers met
+        if (i >= j)
+            return j;
+
+        std::swap(values[i], values[j]);
+    }
+}
+
+int randomizedPartition3(std::vector<size_t>& values, int l, int r)
+{
+    int n = r - l + 1;
+    int pivot = rand() % n;
+    std::swap(values[l + pivot], values[r]);
+
+    int x = values[r], i = l;
+    for (int j = l; j <= r - 1; j++)
+    {
+        if (values[j] <= x)
+        {
+            std::swap(values[i], values[j]);
+            i++;
+        }
+    }
+    std::swap(values[i], values[r]);
+    return i;
+}
+
+int randomizedSelect(std::vector<size_t> values, int p, int r, int i)
+{
+    /*
+    // Partition the array around a random element and
+    // get position of pivot element in sorted array
+    int pos = randomizedPartition(values, p, r);
+
+    // If position is same as k
+    if (pos - p == i - 1)
+        return values[pos];
+    if (pos - p > i - 1)  // If position is more, recur for left subarray
+        return randomizedSelect(values, p, pos - 1, i);
+
+    // Else recur for right subarray
+    return randomizedSelect(values, pos + 1, r, i - pos + p - 1);
+    */
+
+    // Pseudo code Alux Nimmervoll, Algo vo3
+    // Anmerkung: code funktioniert!
+    /*
+    RANDOMIZED-SELECT(A,p,r,i)
+        if (p==r) then return A[p]
+        q=RANDOMIZED_PARTITION(A,p,r) //Pivot Element A[q]
+        k=q-p+1 //Anzahl Elemente A[p..q]
+        if (i==k) then return A[q] //Pivot ist das gesuchte
+        elseif (i<k)
+        then return RANDOMIZED-SELECT(A,p,q-1,i)
+        else return RANDOMIZED-SELECT(A,q+1,r,i-k)
+    */
+
     if (p == r) return values[p];
 
-    size_t q = randomizedPartition(values, p, r); // Pivot Element A[q]
+    //int q = randomizedPartition(values, p, r); // Pivot Element A[q]
-    size_t k = q - p + 1; // Anzahl Elemente A[p..q]
+    //int q = randomizedPartition2(values, p, r); // Pivot Element A[q]
+    int q = randomizedPartition3(values, p, r); // Pivot Element A[q]
+    int k = q - p + 1; // Anzahl Elemente A[p..q]
     if (i == k) return values[q]; // Pivot ist das gesuchte
     else if (i < k)
         return randomizedSelect(values, p, q - 1, i);