Wednesday, 16 October 2013

CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS - ANNA UNIV 1ST SEM REG 2013 ME CSE SYLLABUS



CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS - ANNA UNIV 1ST SEM REG 2013 ME CSE SYLLABUS

ANNA UNIVERSITY, CHENNAI
REGULATIONS - 2013
M.E. COMPUTER SCIENCE AND ENGINEERING
CP7102 ADVANCED DATA STRUCTURES AND ALGORITHMS

OBJECTIVES:
 To understand the principles of iterative and recursive algorithms.
 To learn the graph search algorithms.
 To study network flow and linear programming problems.
 To learn the hill climbing and dynamic programming design techniques.
 To develop recursive backtracking algorithms.
 To get an awareness of NP completeness and randomized algorithms.
 To learn the principles of shared and concurrent objects.
 To learn concurrent data structures.

UNIT I ITERATIVE AND RECURSIVE ALGORITHMS
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 OPTIMISATION ALGORITHMS
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
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-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
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
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

OUTCOMES:
Upon completion of the course, the students will be able to
 Design and apply iterative and recursive algorithms.
 Design and implement optimisation algorithms in specific applications.
 Design appropriate shared objects and concurrent objects for applications.
 Implement and apply concurrent linked lists, stacks, and queues.

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. 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.

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