Due: Friday, Jan 30th in class Late assignments will be penalized 20% per day.

Book Questions from Introduction to Algorithms - 3rd ed.

1.2-2, 1.2-3

2.2-3, 2-2

Insertion sort implementation.

Hints:

1.2-2 & 1.2-3 Remember that n must be an integer.

2.2-3 Be sure to give a mathematically rigorous justification for your answer and not simply an intuitive explanation. Consider what the probability is for the i^th element being the desired one and how many elements were searched to find it.

2-2 (a) - Consider what two criteria are necessary for a sorting algorithm to be correct (the obvious one is that the elements end up in non-decreasing order, what is the other?)

(b) - What must be true both before and after the inner loop executes (consider what the inner loop does)? Remember you must show it holds for initialization, maintenance, and termination conditions.

(c) - What must be true both before and after the outer loop executes (consider what the outer loop does)? Remember you must show it holds for initialization, maintenance, and termination conditions.

(d) - Note this version of bubble-sort uses fixed iteration loops, i.e. no while statements.

Implementation

A skeleton project is provided in CS360_Sorter_Insert.zip. The zip file contains both a Visual Studio 2013 project and a Linux/OSX makefile to compile the code. Sorter.cpp contains both utility functions as well as empty sort function stubs - you should not need to modify main() or any of the utility functions.

• For each input size, the program generates a random array D[]
• D[] is copied into the array A[] prior to each sorting function call (such that each sort works on the same data sets)
• You may wish to uncomment the print_array() call after writing each sort to test your code for n=16 and NUM_AVG=1 to verify the sort is working correctly
• Since C++ does not have an A.length member variable, I have included a function called length(A) which will return the length of the array (which is stored in A[0])
• All arrays have been expanded by 1 (with appropriate adjustments to any loops) to agree with the pseudocode from the book where array indices range from A[1] -> A[n]

Your Task

Implement the sort algorithm as given in the pseudocode below for insertion sort. Insert counter increment statements (note: a count global variable is provided), into each sorting function for each executable line of pseudocode (e.g. count all three lines required to implement a swap as a single operation). Use this counter to empirically measure the runtime of each sort. Only increment the counter for statements within the sorting functions, i.e. do not include any initialization overhead incurred in main() or the utility functions. Note that count is reset prior to each sort call but the results are stored in a 2D array counter which is used to display a table of all results once all the sorts and runs have completed.

Generate runs for 13 input sizes using increasing powers of 2 from 2⁴ = 16 to 2¹⁶ = 65536.

The #define NUM_AVG sets the number of data sets of each size to generate in order to compute an average runtime for each size. This value should be set to a reasonable number, e.g. 10, to give a good approximation of the average runtime of each sort. Note that the larger the value that is chosen, the longer the program will take to run.

You should generate tables for two different input ranges

• Set #define MAX_RANGE 32768 (giving elements in the range [1 -> 32768])
• Set #define MAX_RANGE 1024 (giving elements in the range [1 -> 1024])

Once the data for all input sizes and element ranges have been generated, make a meaningful plot (e.g. using Excel) of the data showing important characteristics. In particular:

• Plot number of inputs n vs. empirical average runtimes as data points
• Show the best fit asymptotic curve for cn² appropriate for the sort. Determine an approximate value of c to the nearest 0.5 for each sort that fits the actual data relatively well. (Hint: Simply manually choose values for each c and plot the corresponding asymptotic curve until it fits the data reasonably well, i.e. you do not need to mathematically find the "best-fit" values.)

Insertion Sort

INSERTION-SORT(A)
1  for j = 2 to A.length
2     key = A[j]
3     // Insert A[j] into the sorted sequence A[1..j-1]
4     i = j - 1
5     while i > 0 and A[i] > key
6        A[i+1] = A[i]
7        i = i - 1
8     A[i+1] = key