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A.V.C College of Engineering
Department of Computer Science & Engineering
2014 Odd Semester
Lesson Plan
SYLLABUS
CP7102 AD...
Completeness-Satisfiability-Proving NP-Completeness-3-Coloring- Bipartite
Matching. Randomized Algorithms-Randomness to Hi...
3. Steven S. Skiena, “The Algorithm Design Manual”, Springer, 2008.
4. Peter Brass, “Advanced Data Structures”, Cambridge ...
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  1. 1. A.V.C College of Engineering Department of Computer Science & Engineering 2014 Odd Semester Lesson Plan SYLLABUS CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS L T P C 3 0 0 3 UNIT I ITERATIVE AND RECURSIVE ALGORITHMS 9 Iterative Algorithms: Measures of Progress and Loop Invariants-Paradigm Shift: Sequence of Actions versus Sequence of Assertions- Steps to Develop an Iterative Algorithm-Different Types of Iterative Algorithms--Typical Errors-Recursion-Forward versus Backward- Towers of Hanoi-Checklist for Recursive Algorithms-The Stack Frame-Proving Correctness with Strong Induction- Examples of Recursive Algorithms-Sorting and Selecting Algorithms-Operations on Integers- Ackermann’s Function- Recursion on Trees-Tree Traversals-Examples- Generalizing the Problem - Heap Sort and Priority Queues-Representing Expressions. UNIT II OPTIMIZATION ALGORITHMS 9 Optimization Problems-Graph Search Algorithms-Generic Search-Breadth- First Search-Dijkstra’s Shortest-Weighted-Path -Depth-First Search-Recursive Depth-First Search-Linear Ordering of a Partial Order- Network Flows and Linear Programming-Hill Climbing-Primal Dual Hill Climbing- Steepest Ascent Hill Climbing-Linear Programming-Recursive Backtracking- Developing Recursive Backtracking Algorithm- Pruning Branches- Satisfiability UNIT III DYNAMIC PROGRAMMING ALGORITHMS 9 Developing a Dynamic Programming Algorithm-Subtle Points- Question for the Little Bird-Subinstances and Subsolutions-Set of Substances-Decreasing Time and Space-Number of Solutions-Code. Reductions and NP-
  2. 2. Completeness-Satisfiability-Proving NP-Completeness-3-Coloring- Bipartite Matching. Randomized Algorithms-Randomness to Hide Worst Cases- Optimization Problems with a Random Structure. UNIT IV SHARED OBJECTS AND CONCURRENT OBJECTS 9 Shared Objects and Synchronization -Properties of Mutual Exclusion-The Mora l- The Producer–Consumer Problem -The Readers–Writers Problem- Realities of Parallelization-Parallel Programming- Principles- Mutual Exclusion-Time- Critical Sections—Thread Solutions-The Filter Lock- Fairness-Lamport’s Bakery Algorithm-Bounded Timestamps-Lower Bounds on the Number of Locations-Concurrent Objects- Concurrency and Correctness-Sequential Objects-Quiescent Consistency- Sequential Consistency-Linearizability- Formal Definitions- Progress Conditions- The Java Memory Model UNIT V CONCURRENT DATA STRUCTURES 9 Practice-Linked Lists-The Role of Locking-List-Based Sets-Concurrent Reasoning- Coarse-Grained Synchronization-Fine-Grained Synchronization- Optimistic Synchronization- Lazy Synchronization-Non-Blocking Synchronization-Concurrent Queues and the ABA Problem- Queues-A Bounded Partial Queue-An Unbounded Total Queue-An Unbounded Lock- Free Queue-Memory Reclamation and the ABA Problem- Dual Data Structures- Concurrent Stacks and Elimination- An Unbounded Lock-Free Stack- Elimination-The Elimination Backoff Stack TOTAL: 45 PERIODS REFERENCES: 1. Jeff Edmonds, “How to Think about Algorithms”, Cambridge University Press, 2008. 2. M. Herlihy and N. Shavit, “The Art of Multiprocessor Programming”, Morgan Kaufmann, 2008.
  3. 3. 3. Steven S. Skiena, “The Algorithm Design Manual”, Springer, 2008. 4. Peter Brass, “Advanced Data Structures”, Cambridge University Press, 2008. 5. S. Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, McGrawHill, 2008. 6. J. Kleinberg and E. Tardos, "Algorithm Design“, Pearson Education, 2006. 7. T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, “Introduction to Algorithms“,PHI Learning Private Limited, 2012. 8. Rajeev Motwani and Prabhakar Raghavan, “Randomized Algorithms”, Cambridge University Press, 1995. 9. A. V. Aho, J. E. Hopcroft, and J. D. Ullman, “The Design and Analysis of Computer Algorithms”, Addison-Wesley, 1975. 10. A. V. Aho, J. E. Hopcroft, and J. D. Ullman,”Data Structures and Algorithms”, Pearson, 2006. A.V.C College of Engineering Department of Computer Science & Engineering 2014 Odd Semester Lesson Plan Name of the Staff: M. Parvathi Class: I M.E(CSE) SUB: CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS SEM: I UNIT I ITERATIVE AND RECURSIVE ALGORITHMS S. No Topics and Sub Topics Ref Book No Page No Periods Required 1 Iterative Algorithms: Measures of Progress and Loop Invariants T1 5-27 2 Paradigm Shift: Sequence of Actions versus Sequence of Assertions Steps to Develop an Iterative Algorithm Different Types of Iterative Algorithms Typical Errors
  4. 4. 6 Recursion T1 97-112 2 Forward versus Backward Towers of Hanoi Checklist for Recursive Algorithms The Stack Frame Proving Correctness with Strong Induction 12 Examples of Recursive Algorithms T1 114- 130 2 Sorting and Selecting Algorithms Operations on Integers Ackermann’s Function 16 Recursion on Trees T1 130- 153 3 Tree Traversals Examples Generalizing the Problem Heap Sort and Priority Queues Representing Expressions Total Periods 9 UNIT II OPTIMIZATION ALGORITHMS S. No Topics and Sub Topics Ref Book No Page No Periods Required 1. Optimization Problems T1 171- 173 1 2. Graph Search Algorithms T1 173- 196 3 Generic Search Breadth-First Search Dijkstra’s Shortest-Weighted- Path Depth-First Search Recursive Depth-First Search Linear Ordering of a Partial Order 9. Network Flows and Linear Programming T1 198- 223 3
  5. 5. Hill Climbing Primal Dual Hill Climbing Steepest Ascent Hill Climbing Linear Programming 14. Recursive Backtracking T1 251- 265 2 Developing Recursive Backtracking Algorithm Pruning Branches Satisfiability Total Periods 9 UNIT III DYNAMIC PROGRAMMING ALGORITHMS S. No Topics and Sub Topics Ref Book No Page No Periods Required 1. Developing a Dynamic Programming Algorithm T1 267- 277 1 2. Subtle Points T1 277- 295 4 Question for the Little Bird Subinstances and Subsolutions Set of Substances Decreasing Time and Space Number of Solutions The New Code 9. Reductions and NP- Completeness T1 324- 342 2 Satisfiability Proving NP-Completeness 3-Coloring Bipartite Matching 14. Randomized Algorithms T1 346- 356 2 Randomness to Hide Worst Cases Optimization Problems with a Random Structure Total Periods 9 UNIT IV SHARED OBJECTS AND CONCURRENT OBJECTS S. Topics and Sub Topics Ref Book Page Periods
  6. 6. No No No Required 1. Introduction T2 1-19 3 Shared Objects and Synchronization Properties of Mutual Exclusion The Moral The Producer–Consumer Problem The Readers–Writers Problem Realities of Parallelization Parallel Programming 2. Principles T2 19-45 3 Mutual Exclusion Time Critical Sections Thread Solutions The Filter Lock Fairness Lamport’s Bakery Algorithm Bounded Timestamps Lower Bounds on the Number of Locations 3. Concurrent Objects T2 45-65 3 Concurrency and Correctness Sequential Objects Quiescent Consistency Sequential Consistency Linearizability Formal Definitions Progress Conditions The Java Memory Model Total Periods 9 UNIT V CONCURRENT DATA STRUCTURES
  7. 7. S. No Topics and Sub Topics Ref Book No Page No Periods Required 1. Linked Lists : The Role of Locking T2 195- 219 4 List-Based Sets Concurrent Reasoning Coarse-Grained Synchronization Fine-Grained Synchronization Optimistic Synchronization Lazy Synchronization Non-Blocking Synchronization 9. Concurrent Queues and the ABA Problem T2 223- 245 3 Queues A Bounded Partial Queue An Unbounded Total Queue An Unbounded Lock-Free Queue Memory Reclamation and the ABA Problem Dual Data Structures 16. Concurrent Stacks and Elimination T2 245- 255 2An Unbounded Lock-Free Stack- Elimination The Elimination Backoff Stack Total Periods 9 Schedule of Tutorial Hours
  8. 8. S. No. Tutorial Hour 1 Unit -1Test Tutorial Hour Topics Covered: 1. Iterative Algorithms 2. Towers of Hanoi-Checklist for Recursive Algorithms, Ackermann’s Function 3. Heap Sort and Priority Queues, Representing Expressions. 2 Unit-II Test Tutorial Hour Topics Covered: 1. Generic Search ,Breadth-First Search ,Dijkstra’s Shortest-Weighted-Path ,Depth-First Search 2. Primal Dual Hill Climbing 3. Developing Recursive Backtracking Algorithm 3 Unit-III Test Tutorial Hour Topics Covered: 1. Subtle Points, Question for the Little Bird,Subinstances and Subsolutions,Set of Substances 2. Reductions and NP-Completeness 3. 3-Coloring,Bipartite Matching, Randomized Algorithms 4 Unit-IV Test Tutorial Hour Topics Covered: 1. The Producer–Consumer Problem ,The Readers– Writers Problem,Realities of Parallelization- Parallel Programming 2. Thread Solutions 3. Concurrent Objects 5 Unit-V Test Tutorial Hour Topics Covered: 1. Linked Lists-The Role of Locking 2. Concurrent Queues and the ABA Problem 3. Concurrent Stacks and Elimination
  9. 9. A.V.C College of Engineering Department of Computer Science & Engineering 2014 Odd Semester Lesson Plan Name of the Staff: M. Parvathi Class: I M.E(CSE) SUB: CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS SEM: I Consolidated Lesson Plan S. No Units Total Periods 1. I 9 2. II 9 3. III 9 4. IV 9 5. V 9 6. Tutorial Hours 5 Grand Total 50 Signature of the Staff Signature of the HOD Signature of the Principal
  10. 10. A.V.C College of Engineering Department of Computer Science & Engineering 2014 Odd Semester Lesson Plan Name of the Staff: M. Parvathi Class: I M.E(CSE) SUB: CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS SEM: I Consolidated Lesson Plan S. No Units Total Periods 1. I 9 2. II 9 3. III 9 4. IV 9 5. V 9 6. Tutorial Hours 5 Grand Total 50 Signature of the Staff Signature of the HOD Signature of the Principal

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