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# Problem Set 1

* Weight: 10% of your final grade
* Due: after Unit 2

Save your answers to the exercises in Microsoft Word, plain text, or PDF files.
When you complete all the exercises of an assignment, zip them into a single file and submit it here.

Submit your solutions to the following exercises and problems:

1. Exercise 1.1-4
  * How are the shortest path and traveling-salesman problems given above similar?
  * How are they different?

    The shortest path problem is looking for an efficient solution that routes
    from point A to point B. The traveling-salesman problem is similar except
    that the sales person needs to visit multiple locations then return to the
    starting point in the most efficient way. These problems are similar because
    the shortest path from point A to B can be used to help determine a good
    enough solution for the traveling-salesman problem.

    Both of these problems are considered an NP-complete problems because it
    hasn't been proven if an efficient algorithm can or cannot exist.


1. Exercise 1.2-2 from the textbook (5 marks)
  * Suppose we are comparing implementations of insertion sort and merge sort on
    the same machine. For inputs of size n, insertion sort runs in 8n^2 steps,
    while merge sort runs in 64nlg(n) steps. For which values of n does
    insertion sort beat merge sort?

    The following program produces a result of '44'.

    ```golang
    func main() {
      fmt.Println("n,isort,msort")

      for n := 2.0; n < 1000.0; n++ {
        isort := 8 * math.Pow(n, 2)
        msort := 64 * (n * math.Log2(n))

        fmt.Printf("%v,%v,%v\n", n, isort, msort)
        if isort > msort {
          break
        }
      }
    }
    ```

    ``csv
    n,isort,msort
    2,32,128
    3,72,304.312800138462
    4,128,512
    5,200,743.0169903639559
    6,288,992.6256002769239
    7,392,1257.6950050818066
    8,512,1536
    9,648,1825.876800830772
    10,800,2126.033980727912
    11,968,2435.439859520657
    12,1152,2753.251200553848
    13,1352,3078.7658454933885
    14,1568,3411.390010163613
    15,1800,3750.614971784178
    16,2048,4096
    17,2312,4447.159571280369
    18,2592,4803.753601661543
    19,2888,5165.4798563474
    20,3200,5532.067961455824
    21,3528,5903.274616214654
    22,3872,6278.879719041314
    23,4232,6658.683199315923
    24,4608,7042.502401107696
    25,5000,7430.169903639559
    26,5408,7821.531690986777
    27,5832,8216.445603738473
    28,6272,8614.780020327225
    29,6728,9016.412726956773
    30,7200,9421.229943568356
    31,7688,9829.12547980756
    32,8192,10240
    33,8712,10653.760380085054
    34,9248,11070.319142560738
    35,9800,11489.593957956724
    36,10368,11911.507203323086
    37,10952,12335.985569809354
    38,11552,12762.9597126948
    39,12168,13192.363938280172
    40,12800,13624.135922911648
    41,13448,14058.216460117852
    42,14112,14494.549232429308
    43,14792,14933.080604940173
    44,15488,15373.759438082629
    ```


1. Exercise 2.1-3 from the textbook. (10 marks)

    Consider the searching problem:

    Input: A sequence of n numbers A = {a1, a2, ...., an} and a value v.
    Output: An index i such that v = A[i] or the special value NIL if v does not
    appear in A.

    Write pseudocode for linear search, which scans through the sequence,
    looking for v. Using a loop invariant, prove that your algorithm is correct.
    Make sure that your loop invariant fulfills the three necessary properties.

1. Exercise 2.2-3 from the textbook (10 marks)

    Consider linear search again (see Exercise 2.1-3). How many elements of the
    input sequence need to be checked on the average assuming that the element
    being searched for is equally likely to be any element in the array? How
    about in the worst case? What are the average-case and worst-case running
    times of linear search in O-notation? Justify your answers.

1. Exercise 2.3-5 from the textbook (10 marks)

    Referring back to the searching problem (see Exercise 2.1-3), observe that
    if the sequence A is sorted, we can check the midpoint of the sequence
    against v and eliminate half of the sequence from further consideration. The
    binary search algorithm repeats this procedure, halving the size of the
    remaining portion of the sequence each time. Write pseudocode, either
    iterative or recursive, for binary search. Argue that the worst case running
    time of binary search is O(lg(n)).

1. Exercise 3.1-1 from the textbook (5 marks)
1. Problem 3-1 from the textbook (10 marks)
1. Exercise 4.1-2 from the textbook (10 marks)
1. Exercise 4.2-1 from the textbook (5 marks)
1. Exercise 4.3-2 from the textbook (10 marks)
1. Exercise 4.4-7 from the textbook (10 marks)
1. Exercise 4.5-3 from the textbook (10 marks)