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Advanced Data Structures


 Describe and implement a range of advanced knowledge structures (hash tables, priority queues, balanced search trees, graphs).

 Analyze the area and time quality of the algorithms studied within the course.

 establish completely different|completely different} solutions for a given problem; analyze blessings and downsides to different solutions.

 Demonstrate Associate in Nursing understanding of external memory and external search and sorting algorithms.

 Demonstrate Associate in Nursing understanding of easy Entity-Relationship models for databases.


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


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


PRIORITY QUEUES (HEAPS) Model, straightforward Implementation, Binary Heap-Structure Property-Heap-Order Property-Basic Heap Operations- alternative Heap Operation, Applications of Priority Queues- the choice downside Event Simulation downside, Binomial Queues- Binomial Queue Structure – Binomial Queue Operation- Implementation of Binomial Queues


economical BINARY SEARCH TREES best Binary Search Trees, AVL Trees, Red-Black Trees, Definition- illustration of a Red- Black Tree- looking out a Red-Black Tree- Inserting into a Red Black Tree- Deletion from a Red-Black Tree- connection Red-Black Trees, rending a Red-Black tree.


MULTIWAY SEARCH TREES M-Way Search Trees, Definition Associate in Nursingd Properties- looking out an M-Way Search Tree, B-Trees, Definition and Properties- range of parts during a B-tree- Insertion into B-Tree- Deletion from a B-Tree- B+-Tree Definition- looking out a B+-Tree- Insertion into B+-tree- Deletion from a B+-Tree.
II Year – II Semester L T P C four zero zero three


DIGITAL SEARCH STRUCTURES Digital Search Trees, Definition- Search, Insert and Delete- Binary tries and Patricia, Binary Tries, Compressed Binary Tries- Patricia, Multiway Tries- Definitions- looking out a Trie- Sampling Strategies- Insertion into a Trie- Deletion from a Trie- Keys with totally different Length- Height of a Trie- area needed and different Node Structure- Prefix Search and Applications- Compressed Tries- Compressed Tries With Skip Fields- Compressed Tries With labelled Edges- area needed by a Compressed Tries, Tries and web Packet Forwarding ,IP Routing- 1-Bit Tries- Fixed-Stride Tries-Variable-Stride Tries.


 Be ready to perceive and apply amortised analysis on knowledge structures, together with binary search trees, mergable plenty, and disjoint sets.

 perceive the implementation and quality analysis of basic algorithms like RSA, property testing, max flow, distinct Fourier rework.  Have an inspiration of applications of algorithms during a sort of areas, together with applied mathematics and duality, string matching, game-theory


1. knowledge Structures, a Pseudocode Approach, Richard F Gilberg, Behrouz A Forouzan, Cengage.

2. Fundamentals of knowledge Structures in C++, Ellis pianist, Sartaj Sahni and Dinesh Mehta, second Edition, Universities Press (India) Pvt. Ltd 3. knowledge structures and algorithmic rule Analysis in C++, second Edition, Mark Allen Weiss, Pearson


one. internet : 2. three. four. five. File Structures :An Object destined approach with C++, 3rd ed, Michel J folks, Greg Riccardi, Bill Zoellick vi. C and knowledge Structures: A Snap Shot destined written material with Live examples from Science and Engineering, NB Venkateswarlu Prasad, S Chand, 2010

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