Q1[3 Marks]Introduction
What does the Big-Omega notation determine in algorithm analysis? Explain divide and conquer approach of algorithm.
ENCT 252Bachelor in Computer Engineering · Semester 41 Paper Available
Data Structure and Algorithm
Past examination question papers and complete curriculum syllabus for Data Structure and Algorithm (ENCT 252), Bachelor in Computer Engineering Semester 4 under Institute of Engineering (IOE), Tribhuvan University.
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Complete questions from each exam session (Regular & Back exams from 2082 to 2069) for Data Structure and Algorithm. Click any session paper to expand.
Showing 226 questions across 16 exam session papers
Institute of Engineering • 2083 Baishakh Board Examination
Q2[5 Marks]Tree
How do you delete a node with one child in binary search tree? Create a AVL tree for following sequence of elements: 3, 2, 1, 4, 5, 6, 7, 16, 15, 14, 13, 12. Construct a B-tree of order 3 for given data: 52, 46, 27, 81, 90, 108, 72, 110, 35, 115, 121, 86.
Q3[5 Marks]Tree
Construct a B-tree of order 3 for given data: 52, 46, 27, 81, 90, 108, 72, 110, 35, 115, 121, 86.
Q4[2 Marks]Sorting Algorithms
Define internal and external sorting. Sort the data 81, 89, 9, 11, 14, 76, 54, 22, 49 and 37 using Heap sort. Also define the time and space complexity of heap sort.
Q5[1 Marks]Searching Algorithms
Explain sequential search efficiency. Write algorithm for Binary search. Insert keys 89,18,49,58 and 69 with hash table size 10 using quadratic probing.
Q6[1 Marks]Stack and Recursion
Define stack. Convert the following infix expression to postfix using stack. Infix expression: .
Q7[3 Marks]Stack and Recursion
Construct the recursive call tree for the Tower of Hanoi problem with 3 disks, showing each recursive call to move disks from peg A to peg C using peg B.
Q8[4 Marks]Queues
How circular queue overcomes the problem of linear queue in terms of memory efficiency? What do you mean by priority queue and what are their types?
Q9[3 Marks]Linked List
Differentiate between static and dynamic list with suitable example. Write algorithm to add two polynomials using linked list.
Curriculum Syllabus & Course Topics
Sourced from TU curriculum portalChapter-wise Units & Micro-Syllabus Topics (8 Units)
1. Introduction
- 1.1Introduction to data structures
- 1.1.1Need of data structures
- 1.1.2Types of data structures and its characteristics
- 1.2Abstract data type (ADT)
- 1.3Basics of algorithm design techniques (Brute Force, divide and conquer, Greedy algorithms, branch and bound, backtracking, randomized, recursive, dynamic programming)
- 1.4Algorithm analysis
- 1.4.1Time and space complexity
- 1.4.2Best, worst and average case analysis
- 1.4.3Rate of growth
- 1.4.4Asymptotic notations: Big Oh, Big Omega and Big Theta
2. Stack and Recursion
- 2.1Definition of stack and its operations
- 2.2Array implementation of stack ADT
- 2.3Stack applications
- 2.3.1Expression conversion: Infix to postfix and prefix expression
- 2.3.2Expression evaluation: Infix and postfix expression evaluation
- 2.4Recursion
- 2.4.1Concept of recursion
- 2.4.2Recursion and stack
- 2.4.3Recursion vs iteration
- 2.4.4Execution of recursive calls
- 2.4.5Types of recursions
- 2.4.6Applications of recursion: Tower of Hanoi
3. Queues
- 3.1Definition of queue and its operations
- 3.2Array implementation of queue ADT
- 3.3Types of queue ADT: Linear, circular, double ended and priority queues
4. Linked List
- 4.1Definition of list and its operations
- 4.2Array implementation of list ADT
- 4.3Static list and its limitations
- 4.4Linked list: Definition and its operations
- 4.5Types of linked list: Singly, doubly, circular
- 4.6Application of linked list
- 4.6.1Linked list implementation of stack and queue ADT
- 4.6.2Solving polynomial equations using linked list
5. Tree
- 5.1Definition and tree terminologies
- 5.2Binary trees
- 5.2.1Definition and types
- 5.2.2Array and linked list representation
- 5.2.3Traversal algorithms: Pre-order, in-order and post-order traversal
- 5.2.4Application of full binary tree: Huffman algorithm
- 5.3Binary search tree
- 5.3.1Definition and operations on binary search tree: Insertion, deletion, searching and traversing
- 5.3.2Construction of binary search tree
- 5.4Balanced binary tree
- 5.4.1Problem with unbalanced binary trees
- 5.4.2Balanced binary search tree
- 5.4.3AVL tree, definition and need of AVL tree, construction of AVL tree: Insertion, deletion on AVL tree and rotation operations
- 5.5Introduction to red-black tree
- 5.6B-Tree: Need, definition and construction of B-tree
6. Graphs
- 6.1Definition, terminologies and types of graphs
- 6.2Representation of graphs: Adjacency matrix, incidence matrix and adjacency list
- 6.3Transitive closure and Warshall’s algorithm
- 6.4Graph traversals: Breadth-first search, depth-first search and topological sort
- 6.5Minimum spanning tree: Kruskal’s algorithm and prim’s algorithm
- 6.6Shortest-paths problems: Dijkstra’s algorithm, Floyd- Warshall algorithm
7. Sorting Algorithms
- 7.1Definition of sorting and its applications
- 7.2Types of sorting: Internal/external sort, stable/unstable sort, in-place/ not in- place sort, adaptive/ non-adaptive sort
- 7.3Sorting algorithms and its efficiency: Bubble, insertion, selection, shell, quick, merge, radix and heap sorting
8. Searching Algorithms
- 8.1Definition of searching techniques and its applications
- 8.2Different searching algorithms and its efficiency
- 8.2.1Sequential search
- 8.2.2Binary search
- 8.3Hashing
- 8.3.1Definition and its applications
- 8.3.2Hash function
- 8.3.3Hash table
- 8.3.4Collision in hash table
- 8.3.5Collision resolution techniques: Chaining method and open addressing method (Linear probing, quadratic probing and double hashing)
Examination Scheme & Marks Distribution
Evaluation Structure
- Final Board Theory Exam: 60 Marks (Pass mark: 24)
- Internal Assessment: 40 Marks (Pass mark: 16)
- Practical / Lab Exam: 25 or 50 Marks (Continuous lab evaluation + viva, where applicable)
* This is the general current IOE 60/40 scheme; verify course-specific details in the syllabus above.
Exam Preparation Guidelines
- Review the available past examination paper to understand question styling, typical derivation topics, and marks allocation.
- Practice writing clean algorithms and code implementations, tracing dry runs with sample inputs, and explaining complexity trade-offs.
- Structure answers with labeled diagrams, concise bullet points, and highlight final answers in numerical solutions.
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Curriculum Syllabus & Marking Scheme