Syllabus — Data Structures Lab (AR152)
Official GGSIPU syllabus for the B.Tech Artificial Intelligence and Data Science 2026-30 batch (first year, under USAR), applicable from the academic session 2026-27.
P 2 C 1
Internal Evaluation: as per university examination norms. End Term Practical Examination: as per university examination norms.
Practical component of Data Structures (AR102). The document publishes no separate unit-wise syllabus for this lab; the practical list is notified by the teacher, and the units below are the theory paper's.
Course outcomes (same as AR102)
- Understand data structures, algorithm analysis, searching, and sorting techniques. [K2]
- Apply linear data structures such as arrays, linked lists, stacks, and queues in solving computational problems. [K3]
- Evaluate tree-based data structures and balancing techniques for efficient storage, searching, and sorting. [K5]
- Analyze graph traversal methods, disjoint data structures, and hashing techniques for efficient problem solving. [K4]
Unit I
Introduction to Data Structures: Overview of Data Structures, Data types – primitive and non-primitive, Basics of Algorithms Analysis, Performance Analysis and Measurement (Time and space analysis of algorithms-Average, best and worst case analysis), Asymptotic Notations, Types of Data Structures- Linear & Non Linear Data Structures, Concept of Abstract Data Types. Sorting – Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, Merge Sort, Sequential (Linear) Search and Binary Search
Unit II
Linear Data Structures: Array: Representation of arrays, Applications of arrays: sparse matrix and its representation, polynomials and polynomials arithmetics; Linked List: Singly Linked List, Doubly Linked list, Circular linked list; Applications of linked list: Stack-Definitions & Concepts, Operations On Stacks, Linked List vs Array implementation of Stack; Applications of Stacks: Prefix, Infix and Postfix Expressions; Queue: Representation Of Queue, Operations On Queue, Linked List vs Array implementation of Queue, Circular Queue, Priority Queue.
Unit III
Trees: Tree-Definitions and Concepts, Representation of binary tree, Binary tree traversal (Inorder, postorder, preorder), Binary search trees, Conversion of General Trees To Binary Trees, Applications Of Trees, Balanced trees: AVL trees, Height Balanced Tree, B Tree, B+ Tree; Introduction to Heap, Heap Sort.
Unit IV
Fundamentals of Graphs & Hashing: Disjoint Data Structures, Union-Find Algorithm, Representation Of Graphs, Graph Traversals: Breadth First Search and Depth First Search; Hashing: Hashing Functions, Collision Resolution Techniques.