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Friday, September 30, 2011

DATA STRUCTURES AND ALGORITHMS PPT








DATA STRUCTURE AND ALGORITHMS PPT
 
The specific topics are given below. The number of lectures devoted to each topic is only an estimate. The actual time spent on each topic may be different from the estimate.
  1. Simple sort methods and performance measurement. (2 lectures).
  2. Data representation methods and linear lists. (7 lectures)
  3. Arrays & matrices. (2 lectures)
  4. Stacks. (2 lectures)
  5. Queues. (1 lecture)
  6. Hashing and LZW compression. (3 lectures)
  7. Binary trees. (4 lectures)
  8. Priority queues. (2 lectures)
  9. Tournament trees. (1 lecture)
  10. Search trees. (2 lectures)
  11. Graphs. (3 lectures)
  12. The greedy method. (3 lectures)
  13. Divide-and-conquer. (3 lectures)
  14. Dynamic programming. (5 lectures)
  15. Backtracking. (2 lectures)
  16. Branch-and-bound. (1 lecture) 

  17. .
Lecture Content Reading Slides
1 Course overview and insertion sort. Chapters 1 through 3. Powerpoint
2 Insertion sort and practical complexities. Section 3.5. Powerpoint
3 Run-time measurement. Chapter 4. Powerpoint
4 Linear lists. Sections 5.1-5.2. Powerpoint
5 Array representation and array resizing. Section 5.3. Powerpoint
6 Walk through of code for ArrayLinearList. Section 5.3. Powerpoint
7 Iterators. Linked representation of a linear list. Sections 5.3 and 6.1. Powerpoint
8 Walk through of code for Chain. Head nodes, circular lists, doubly linked lists. Sections 6.2 and 6.3. Powerpoint
9 Simulated pointers and available-space lists. Sections 7.1 and 7.2.Powerpoint
10 Row-major and column-major indexing, and special matrices. Sections 8.1, 8.2, and 8.3. Powerpoint
11 Sparse matrices. Section 8.4. Powerpoint
12 Stacks--application to parentheses matching, towers-of-hanoi, railroad car rearrangement, and switchbox routing; array stacks. Sections 9.1, 9.2, 9.5. Powerpoint
13 Array and linked stacks. Section 9.3 and 9.4. Powerpoint
14 Nonapplicability of queues for parantheses matching, towers-of-hanoi, railroad problem with LIFO tracks, and switchbox routing. Application of queues to railroad problem with FIFO tracks, wire routing, and component labeling. Array and linked queues. Sections 10.1-10.4, 10.5.1-10.5.3. Powerpoint
15 Exam. - -
16 Dictionaries, linear list representation, and hashing. Sections 11.1, 11.2, 11.3, and 11.5. Powerpoint
17 Hashing and hash table design. Section 11.5. Powerpoint
18 LZW compression. Section 11.6. Powerpoint
19 Trees, binary trees, and properties. Sections 12.1-12.3. Powerpoint
20 Binary tree representation and operations. Sections 12.4 and 12.5. Powerpoint
21 Binary tree traversal methods-- preorder, inorder, postorder, level order. Reconstruction from two orders Sections 12.6-12.8. Powerpoint
22 Online equivalence classes. Section 12.9.2. Powerpoint
23 Application of priority queues to heap sort and machine scheduling. Min and max heaps. Sections 13.1-13.3, 13.6.1, and 13.6.2. Powerpoint
24 Initialization of min and max heaps. Height- and weight-biased leftist trees. Sections 13.4.4 and 13.5. Powerpoint
25 Winner and loser trees and application to k-way merging, run generation, and first-fit bin packing. Chapter 14. Powerpoint
26 Binary search trees and indexed binary search trees. Sections 15.1-15.5. Powerpoint
27 Definition of AVL trees. Graph applications and properties. Sections 16.1, 17.1-17.3. Powerpoint
28 Graph operations and representation. Sections 17.4-17.7. Powerpoint
29 Breadth-first and depth-first search. Application to path finding, connected components, and spanning trees. Sections 17.8 and 17.9. Powerpoint
30 Greedy method and application to bin packing, loading, and knapsack problems. Sections 18.1, 18.2, 18.3.1, and 18.3.2. Powerpoint
31 Exam. - -
32 Single source all destinations shortest paths algorithm. Section 18.3.5. Powerpoint
33 Kruskal's and Prim's minimum-cost spanning tree algorithms. Section 18.3.6. Powerpoint
34 Divide and conquer, and application to defective chessboard and min-max problem. Iterative min-max implementation. Sections 19.1 and 19.2.1. Powerpoint
35 Merge sort, natural merge sort, and quick sort. Sections 19.2.2 and 19.2.3. Powerpoint
36 Selection and closest pair of points. Sections 19.2.4 and 19.2.5. Powerpoint
37 Dynamic programming, 0/1 knapsack problem, recursive and iterative solutions. Sections 20.1 and 20.2.1. Powerpoint
38 Matrix multiplication chains, dynamic programming recurrence, recursive solution. Section 20.2.2. Powerpoint
39 Iterative solution to matrix multiplication chains. Section 20.2.2. Powerpoint
40 All pairs shortest paths. Section 20.2.3. Powerpoint
41 Single source shortest paths with negative edge weights. Section 20.2.4. Powerpoint
42 Solution space trees and backtracking. Section 21.1. Powerpoint
43 Branch and bound. Section 22.1. Powerpoint
 

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