Lecture Notes For All: Data Structures and Algorithm Analysis Lectures Video

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Thursday, March 11, 2010

Data Structures and Algorithm Analysis Lectures Video

Data Structures, Algorithms, and Applications in Java

by

Sartaj Sahni

Real Video Lectures

Lecture Content Reading Video

1
Course overview and insertion sort. Chapters 1 through 3. Not Available
2 Insertion sort and practical complexities. Section 3.5. Not Available
3 Run-time measurement. Chapter 4. Not Available
4 Linear lists. Sections 5.1-5.2. Not Available
5 Array representation and array resizing. Section 5.3.

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6 Walk through of code for ArrayLinearList. Section 5.3.

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7 Iterators. Linked representation of a linear list. Sections 5.3 and 6.1.

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8 Walk through of code for Chain. Head nodes, circular lists, doubly linked lists. Sections 6.2 and 6.3. Not Available
9 Simulated pointers and available-space lists. Sections 7.1 and 7.2.

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10 Row-major and column-major indexing, and
special matrices.
Sections 8.1, 8.2, and 8.3.

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11 Sparse matrices. Section 8.4.

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12 Stacks--application to parentheses matching, towers-of-hanoi,
railroad car rearrangement, and switchbox routing;
array stacks.
Sections 9.1, 9.2, 9.5.

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13 Array and linked stacks. Section 9.3 and 9.4.

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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.

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15 Exam. - -
16 Dictionaries, linear list representation, and hashing. Sections 11.1, 11.2, 11.3, and 11.5.

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17 Hashing and hash table design. Section 11.5.

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18 LZW compression. Section 11.6.

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19 Trees, binary trees, and properties. Sections 12.1-12.3. Not Available
20 Binary tree representation and operations. Sections 12.4 and 12.5. Not Available
21 Binary tree traversal methods-- preorder, inorder, postorder,
level order. Reconstruction from two orders
Sections 12.6-12.8.

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22 Online equivalence classes. Section 12.9.2.

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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.

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24 Initialization of min and max heaps.
Height- and weight-biased leftist trees.
Sections 13.4.4 and 13.5.

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25 Winner and loser trees and application to k-way merging, run generation,
and first-fit bin packing.
Chapter 14.

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26 Binary search trees and indexed binary search trees. Sections 15.1-15.5. Not Available
27 Definition of AVL trees. Graph applications and properties. Sections 16.1, 17.1-17.3.

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28 Graph operations and representation. Sections 17.4-17.7.

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29 Breadth-first and depth-first search.
Application to path finding, connected components, and
spanning trees.
Sections 17.8 and 17.9.

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30 Greedy method and application to bin packing, loading,
and knapsack problems.
Sections 18.1, 18.2, 18.3.1, and 18.3.2.

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31 Exam. - -
32 Single source all destinations shortest paths algorithm. Section 18.3.5.

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33 Kruskal's and Prim's minimum-cost spanning tree algorithms. Section 18.3.6.

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34 Divide and conquer, and application to
defective chessboard and min-max problem.
Iterative min-max implementation.
Sections 19.1 and 19.2.1.

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35 Merge sort, natural merge sort, and quick sort. Sections 19.2.2 and 19.2.3.

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36 Selection and closest pair of points. Sections 19.2.4 and 19.2.5.

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37 Dynamic programming, 0/1 knapsack problem, recursive
and iterative
solutions.
Sections 20.1 and 20.2.1.

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38 Matrix multiplication chains, dynamic programming recurrence,
recursive solution.
Section 20.2.2.

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39 Iterative solution to matrix multiplication chains. Section 20.2.2.

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40 All pairs shortest paths. Section 20.2.3.

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41 Single source shortest paths with negative edge weights. Section 20.2.4.

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42 Solution space trees and backtracking. Section 21.1.

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43 Branch and bound. Section 22.1.

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