Syllabus — Data Structures (ICT-116T)
Official GGSIPU syllabus for the B.Tech 2026-30 batch (first year, under USICT), applicable from the academic session 2026-27.
L 3 C 3
Teachers Continuous Evaluation: 40 marks. Term-End Semester Examination: 60 marks.
Course outcomes
- To be able to understand difference between structured data and data structure
- To be able to create common basic data structures and trees
- To have a knowledge of sets, heaps and graphs
- To have basic knowledge of sorting and searching algorithms
Unit I
Abstract Data Types (specification, performance implications), growth of functions and asymptotic analysis, Master’s theorem (without proof). Analysis of array vs linked representations of lists/stacks/queues, Sparse Matrices (transpose and multiplication), Comparison-based sorting: insertion, shell, merge, quick, heap sort — algorithm and comparisons, Time and space complexity, Stability and adaptivity of sorts, Sorting in practice: library sorting functions, Sorting linked lists, Divide and conquer review via mergesort/quick sort, Introduction to non-comparison-based sorting (counting, radix — concept only).
Unit II
Binary trees: traversal techniques, recursive vs non-recursive, Binary Search Trees (BST): insertion, deletion, search, AVL Trees: balancing, rotations, complexity, Heaps and priority queues: heapify, build-heap, insert/delete, Applications: expression trees, interval trees, use of recursion and stack in tree processing, Performance trade-offs among tree variants.Multi-way search trees: m-ary search tree, B-Trees (order, height, node structure, insertion, deletion), B+ Trees (leaf-level chaining, indexing applications), Search operations in B+ Trees
Unit III
Hash tables: hash function design, collision handling (chaining, open addressing), Load factor, rehashing strategies, Dictionary ADT and map APIs, Trie data structure: insertion, search, memory model, Disjoint Sets (Union-Find) with path compression and union by rank, Bit-fields and memory efficiency
Unit IV
Graph representations: adjacency list, adjacency matrix, edge list, Graph traversal algorithms (BFS, DFS) and applications (cycle detection, component labeling), Minimum Spanning Tree (Kruskal, Prim), Shortest paths (Dijkstra, Bellman-Ford), Graph design for real applications (idea of social networks, compiler dependency graphs)
Textbooks
- Data Structures and Algorithm Analysis in C, Mark Allen Weiss, Pearson Education India, Latest Edition.
- Fundamentals of Data Structures in C, Ellis Horowitz, Sartaj Sahni, Susan Anderson-Freed, Universities Press (India) Pvt. Ltd., 2008
References
- Data Structures with C, Seymour Lipschutz, McGraw-Hill Education, 2 Edition 2014
- Data Structures and Algorithms, Alfred V. Aho, Jeffrey D. Ullman, John E. Hopcroft, Addison-Wesley, 1983
- Data Structures: A Pseudocode Approach with C, Richard Gilberg , Behrouz A. Forouzan Cengage Learning, Latest Edition
- Data Structures and Program Design in C, Robert Kruse, Pearson, Latest Edition
- Data structures using C, Y. Langsam, M. J. Augenstein and A. M. Tanenbaum, PHI