Advanced Data Structures Training

OBJECTIVES:

– <!–[endif]–>Describe and implement a variety of advanced data structures (hash tables, priority queues, balanced search trees, graphs).

– Analyze the space and time complexity of the algorithms studied in the course.

– <!–[endif]–>Identify different solutions for a given problem; analyze advantages and disadvantages to different solutions.

– <!–[endif]–>Demonstrate an understanding of external memory and external search and sorting algorithms.

– <!–[endif]–>Demonstrate an understanding of simple Entity-Relationship models for databases.

Unit-I :

Sorting: External Sorting, Introduction, K-way Merging – Buffer Handling for parallel Operation- Run Generation- Optimal Merging of Runs.

UNIT-II:

HASHING: Introduction-Static Hashing- Hash Table- Hash Functions- Secure Hash Function- Overflow Handling- Theoretical Evaluation of Overflow Techniques, Dynamic Hashing- Motivation for Dynamic Hashing -Dynamic Hashing Using Directories- Directory less Dynamic, Hashing,

UNIT-III:
PRIORITY QUEUES (HEAPS): Model, Simple Implementation, Binary Heap-Structure Property-Heap-Order Property-Basic Heap Operations- Other Heap Operation, Applications of Priority Queues- The Selection Problem Event Simulation Problem, Binomial Queues- Binomial Queue Structure – Binomial Queue Operation- Implementation of Binomial Queues

UNIT-IV:

EFFICIENT BINARY SEARCH TREES: Optimal Binary Search Trees, AVL Trees, Red-Black Trees, Definition- Representation of a Red- Black Tree- Searching a Red-Black Tree- Inserting into a Red Black Tree- Deletion from a Red-Black Tree- Joining Red-Black Trees, Splitting a Red-Black tree.

UNIT-V:

MULTIWAY SEARCH TREES: M-Way Search Trees, Definition and Properties- Searching an M-Way Search Tree, B-Trees, Definition and Properties- Number of Elements in a B-tree- Insertion into B-Tree- Deletion from a B-Tree- B+-Tree Definition- Searching a B+-Tree- Insertion into B+-tree- Deletion from a B+-Tree.