Consider the following code for Merge Sort. public > void sort(T[] table) { // BASE CASE - A table with one element is sorted already. if (table.length <= 1) return; // GENERAL CASE - divide-and-conquer int halfSize = table.length/2; // Split table into halves. T[] leftTable = (T[]) new Comparable[halfSize]; T[] rightTable = (T[]) new Comparable[table.length - halfSize]: // copy original data into the two smaller arrays System.arraycopy(table, 0, leftTable, O, halfSize); System.arraycopy(table, halfSize, rightTable, O, table.length - halfSize); sort(leftTable); // recursively sort the left half sort(rightTable); // recursively sort the right half // Merge the halves together back into table merge(table, leftTable, rightTable); } In the class lectures we used sample data with n = 8. The value 8 divides in half very nicely. Suppose the size of the original array is n = 81. How many data items are placed in the LEFT sub-problem? How many data items are placed in the RIGHT sub-problem? Enter your answer as a pair of numbers, such as 23, 72

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Consider the following code for Merge Sort.
public <T extends Comparable<T>> void sort(T] table)
{
// BASE CASE - A table with one element is sorted already.
if (table.length <= 1)
return;
// GENERAL CASE - divide-and-conquer
int halfSize = table.length/2; // Split table into halves.
T[] leftTable = (T[]) new Comparable[halfSize];
T[] rightTable = (T[]) new Comparable[table.length - halfSize];
// copy original data into the two smaller arrays
System.arraycopy(table, 0, leftTable, O, halfSize);
System.arraycopy(table, halfSize, rightTable, O, table.length - halfSize);
sort(leftTable); // recursively sort the left half
sort(rightTable); // recursively sort the right half
// Merge the halves together back into table
merge(table, leftTable, rightTable);
}
In the class lectures we used sample data with n = 8. The value 8 divides in half very nicely.
Suppose the size of the original array is n = 81.
How many data items are placed in the LEFT sub-problem?
How many data items are placed in the RIGHT sub-problem?
Enter your answer as a pair of numbers, such as 23, 72
Transcribed Image Text:Consider the following code for Merge Sort. public <T extends Comparable<T>> void sort(T] table) { // BASE CASE - A table with one element is sorted already. if (table.length <= 1) return; // GENERAL CASE - divide-and-conquer int halfSize = table.length/2; // Split table into halves. T[] leftTable = (T[]) new Comparable[halfSize]; T[] rightTable = (T[]) new Comparable[table.length - halfSize]; // copy original data into the two smaller arrays System.arraycopy(table, 0, leftTable, O, halfSize); System.arraycopy(table, halfSize, rightTable, O, table.length - halfSize); sort(leftTable); // recursively sort the left half sort(rightTable); // recursively sort the right half // Merge the halves together back into table merge(table, leftTable, rightTable); } In the class lectures we used sample data with n = 8. The value 8 divides in half very nicely. Suppose the size of the original array is n = 81. How many data items are placed in the LEFT sub-problem? How many data items are placed in the RIGHT sub-problem? Enter your answer as a pair of numbers, such as 23, 72
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