CODEBHAVYA โ€ข ADVANCED DATA STRUCTURES

๐Ÿง  Advanced Data Structures

Continue after the completed DSA fundamentals and learn advanced structures, efficient algorithms, implementation techniques and interview-oriented problem solving through Levels 8โ€“21.

๐Ÿ“š Complete DSA Fundamentals First

Searching, Sorting, Linked Lists, Stacks, Queues, Trees and Graphs are covered in the Data Structures course. ADS begins from Level 8 and builds on those foundations.

Review DSA Fundamentals โ†’

Three-Part ADS Learning Path

Follow the levels in order so each advanced topic has the required foundation.

PART 1 โ€ข LEVELS 8โ€“13

๐Ÿ“Š Foundations & Algorithms

Analyze performance and study efficient representations, matching, sorting and searching.

  • Performance Analysis
  • Disjoint Sets
  • Sparse Matrices
  • String Pattern Matching
  • Advanced Sorting
  • Advanced Searching
6 Main Topics
PART 2 โ€ข LEVELS 14โ€“18

๐ŸŒณ Advanced Trees & Hashing

Build balanced, digital and multiway trees, then compare advanced heaps and hashing methods.

  • Balanced Binary Search Trees
  • Digital Search Trees
  • Multiway Search Trees
  • Advanced Heaps
  • Hashing
5 Main Topics
PART 3 โ€ข LEVELS 19โ€“21

๐Ÿ•ธ๏ธ Storage, Graphs & Placement

Connect file organization and graph algorithms with interview-level applications.

  • Files & File Organization
  • Advanced Graph Algorithms
  • Placement Problems
3 Main Topics

Foundations & Algorithms

Strengthen analysis skills before moving to advanced structural techniques.

๐Ÿ“Š

Level 8 โ€” Performance Analysis

Measure and compare the efficiency of algorithms with clear reasons.

Subtopics Covered
  • Time and space complexity
  • Best, average and worst cases
  • O, ฮฉ and ฮ˜ notation
  • Growth-rate comparison
Start Learning
๐Ÿ”—

Level 9 โ€” Disjoint Sets

Maintain non-overlapping groups efficiently using the Union-Find structure.

Subtopics Covered
  • Make-Set, Find and Union
  • Tree representation
  • Path compression
  • Union by rank and size
Start Learning
๐Ÿงฎ

Level 10 โ€” Sparse Matrices

Store and process matrices containing mostly zero values without wasting memory.

Subtopics Covered
  • Triplet representation
  • CSR and CSC formats
  • Transpose and addition
  • Storage comparison
Start Learning
โšก

Level 12 โ€” Advanced Sorting

Compare comparison-based and non-comparison-based sorting algorithms.

Subtopics Covered
  • Merge, Quick and Shell Sort
  • Counting, Radix and Bucket Sort
  • Stability and in-place behavior
  • Algorithm selection
Start Learning
๐ŸŽฏ

Level 13 โ€” Advanced Searching

Choose searching strategies by considering ordering, distribution and access cost.

Subtopics Covered
  • Interpolation Search
  • Jump and Fibonacci Search
  • Exponential Search
  • Skip List searching
Start Learning

Advanced Trees & Hashing

Study structures designed for fast search, update, indexing and priority operations.

๐ŸŒฒ

Level 14 โ€” Balanced BST

Preserve efficient search and update operations by controlling tree height.

Subtopics Covered
  • AVL Trees and rotations
  • Redโ€“Black Trees
  • Splay Trees
  • Tree comparison
Start Learning
โ›ฐ๏ธ

Level 17 โ€” Heaps

Implement priority operations and compare merge-friendly heap structures.

Subtopics Covered
  • Binary Heap and Heap Sort
  • Binomial Heap
  • Fibonacci Heap
  • Complexity comparison
Start Learning
#๏ธโƒฃ

Level 18 โ€” Hashing

Design hash tables and resolve collisions while maintaining efficient access.

Subtopics Covered
  • Hash functions
  • Separate chaining
  • Open addressing
  • Load factor and resizing
Start Learning

Storage, Graphs & Placement

Apply advanced structures to persistent data, networks and interview problems.

๐Ÿง  How to Learn ADS

01
Start from Level 8 after completing DSA.
02
Understand the structure and its purpose.
03
Trace algorithms before studying the C program.
04
Compare time and space complexity with reasons.
05
Solve all practice and interview problems.