1. Dynamic Sets and Data Structures Over the course of an algorithm’s execution, an algorithm may maintain a dynamic set of objects The algorithm will perform operations on this set –Queries –Modifying operations We must choose a data structure to implement the dynamic set efficiently The “correct” data structure to choose is based on –Which operations need to be supported –How frequently each operation will be executed

2. Some Example Operations Search(S,k) Insert(S,x) Delete(S,x) Minimum or Maximum(S) Successor or Predecessor (S,x) Merge(S 1,S 2 )

3. Basic Data Structures/Containers Unsorted Arrays Sorted Array Unsorted linked list Sorted linked list Stack Queue Heap

4. Implementation Questions How can I implement a queue with two stacks? –Running time of enqueue? –Dequeue? How can I implement two stacks in one array A[1..n] so that neither stack overflows unless the total number of elements in both stacks exceeds n?

5. Unsorted Array Sorted Array Unsorted LL Sorted LL Heap Search Insert Delete Max/Min Pred/Succ Merge

6. Case Study: Dictionary Search(S,k) Insert(S,x) Delete(S,x) Is any one of the data structures listed so far always the best for implementing a dictionary? Under what conditions, if any, would each be best? What other standard data structure is often used for a dictionary?

7. Case Study: Priority Queue Insert(S,x) Max(S) Delete-max(S) Is any one of the data structures listed so far always the best for implementing a priority queue? Under what conditions, if any, would each be best?

8. Case Study: Minimum Spanning Trees Input –Weighted, connected undirected graph G=(V,E) Weight (length) function w on each edge e in E Task –Compute a spanning tree of G of minimum total weight Spanning tree –If there are n nodes in G, a spanning tree consists of n-1 edges such that no cycles are formed

9. Prim’s algorithm A greedy approach to edge selection –Initialize connected component N to be any node v –Select the minimum weight edge connecting N to V-N –Dynamic set implementation The nodes in V-N Value of a node is how close it is to any node in N To select minimum weight edge, choose node v with minimum value in dynamic set (Extract minimum) and add v to N When v is added to N, we need to update the value of the neighbors of v in V-N (Decrease key)

10. Maintain dynamic set of nodes in V-N If we started with node D, N is now {C,D} Dynamic set values of other nodes: –A, E, F: infinity –B: 4 –G: 6 Illustration ABC D EFG 1 2 2 3 4 5 5 6 10

11. Node B is added to N; edge (B,C) is added to T Need to update dynamic set values of A, E, F –Decrease-key operation Dynamic set values of other nodes: –A: 1 –E: 2 –F: 5 –G: 6 Updating Dynamic Set ABC D EFG 1 2 2 3 4 5 5 6 10

12. Node A is added to N; edge (A,B) is added to T Need to update dynamic set values of E –Decrease-key operation Dynamic set values of other nodes: –E: 2 (unchanged because 2 is smaller than 3) –F: 5 –G: 6 Updating Dynamic Set ABC D EFG 1 2 2 3 4 5 5 6 10

13. Dynamic Set Analysis How many objects in initial dynamic set representation of V-N? Time to build this dynamic set? How many extract-min operations need to happen? How many decrease-key operations may occur? Given all of the above, choose a data structure and tell me the implementation cost.