1. February 4, 2005 Searching and Sorting Arrays

2. Searching

3. The Problem Given an array of elements and a particular element, determine whether that element is in the array.

4. Linear Search One obvious approach is to simply check every element in the array. Pros: conceptually simple easy to implement Cons: slow for large arrays

5. int linearSearch(int list[], int numElements, int value) { int index=0; int position = -1; bool found = false; while (index < numElements && !found) { if (list[index] == value) { found = true; position = index; } index++; } return position; }

6. Binary Search The binary search is cleverer than linear search. Pros: Fast Fairly easy to implement Cons: Values in array need to be in order

7. int binarySearch(int array[], int numElems, int value) { int first = 0; int last = numElems-1; int middle; int position = -1; bool found = false; while (!found && first <=last) { middle = (first+last)/2; //calculate middle point if (array[middle]==value) { found = true; position = middle; } else if (array[middle]>value) { last = middle-1; } else { first = middle +1; } return position; }

8. Sorting

9. The Problem Given an array of elements, put them in order.

10. There are many ways to do this. The various ways differ in execution speed, conceptual simplicity and in how easy they are to implement.

11. Bubble Sort Pro: Simplest way to sort Con: Slowest way

12. The Idea First put the elements one and two in order. Then put elements two and three in order. Then put elements three and four in order. Etc. After this process is over, you can be assured of one thing – The largest element is in the last position.

13. The Idea Now forget about the largest element and repeat the previous process on the remaining elements. After n-1 times, where n is the number of elements in the array, the array will be sorted.

14. Of course it may be sorted before n-1 times, but you can’t guarantee that. We say n-1 times is the worst case scenario.

15. #include using namespace std; void bubbleSort(int array[], int elems) { bool swap; int temp; do { swap = false; for (int count =0; count < (elems-1); count++) { if (array[count] > array[count+1]) { temp = array[count]; array[count]=array[count+1]; array[count+1]=temp; swap=true; } } while (swap); } int main() { int values[] = {2,7,3,6,1}; bubbleSort(values, 5); for (int i=0; i<5; i++) { cout << values[i] << " "; } cout << endl; system("PAUSE"); return 0; }

16. Application to 3n+1 Problem Statement of Problem: Take a positive integer. If it is even, divide it by 2. If it is odd, multiply it by 3 and add 1 Do this recursively: Stop if you get to 1. e.g. 5 -> 16 -> 8 -> 4 -> 2 -> 1

17. Examples 17 -> 52 -> 26 -> 13 -> 40 -> 20 -> 10 -> 5 We can stop here because we did 5 already 9->28->14 -> 7 -> 22 -> 11 -> 34 -> 17 The sequence for 27 takes 111 steps to get to 1

18. Question: Is there a number that does not go to 1. This question was first asked in 1937. It remains unsolved. All numbers up to 2 * 2^58 have been checked as of December 16, 2004

19. If there are no such numbers, the problem is to prove it. Some have said this problem is to hard for modern day mathematics and computer science.

20. Application of Searching to 3n+1 Write a function that takes a positive integer as an input and returns the number of steps it takes to get to 1. If it doesn’t go to 1 (!), the function will never return. Then create an array of one million random integers, and a parallel array of the number of steps to 0 for that random integer. Using a search algorithm, you can investigate what sorts of numbers are in the second array. Perhaps there is a pattern.

21. Next Monday Faster sorting algorithms