RTU Kota B.Tech AI 3rd Semester Data Structures and Algorithms Question Paper 2026

RTU Artificial Intelligence Data Structures and Algorithms 2026 Paper Review

Preparing for the Rajasthan Technical University B.Tech Data Structures and Algorithms exam requires a strong command of memory management and algorithmic efficiency. For students in the Artificial Intelligence branch, this subject dictates how efficiently your machine learning models process massive datasets. Neural networks, decision trees, and knowledge graphs rely completely on underlying data structures like matrices, trees, and graphs. The 2026 paper tests your ability to write clean algorithms, analyze time complexities, and select the correct storage structures for complex data logic. Reviewing this specific branch paper shows you exactly how examiners structure the questions and allocate marks among the programming modules. This preparation allows you to approach your third-semester exam confidently.

Understanding the AI Branch Exam Pattern

The RTU theory examination is a three-hour paper worth 70 marks. The paper consists of three distinct sections designed to evaluate both theoretical clarity and practical coding capability.

• Part A: This section contains ten compulsory questions worth two marks each. You must write short definitions, calculate the exact Big-O complexity of a code snippet, or explain a specific pointer structure under 30 words.
• Part B: You will find seven questions here. You must answer five of them. Each question is worth four marks. Your answers require writing short algorithmic steps, explaining specific operations like tree rotations, or tracing array changes.
• Part C: This section offers five major questions. You need to answer three. Each question carries ten marks. These require writing complete programming logic, executing complex step-by-step algorithms, or proving structural theorems.

Core Topics Evaluated in the AI Paper

The 2026 question paper covers several critical modules that form the backbone of modern computational logic. Focus your study time on these specific areas to maximize your score.

Arrays, Link Lists, and Memory Matrices

This module tests your understanding of linear data storage. You must know how multi-dimensional arrays map to a single-dimensional memory space using Row Major and Column Major ordering formulas. For artificial intelligence applications, arrays form the basis of tensor operations. Practice implementing singly, doubly, and circular linked lists. Examiners frequently ask you to write functions for inserting or deleting nodes at specific positions within a list.

Stacks, Queues, and State Recursion

You need to understand the structural execution of data. Master the array and linked list implementations of stacks and queues. Focus heavily on applications of stacks, such as converting an expression from infix to postfix notation and evaluating postfix expressions. For queues, practice circular queue operations and priority queues. Priority queues are highly relevant to AI search algorithms where certain pathways require immediate processing based on cost parameters.

Non-Linear Structures: Trees

Trees represent hierarchical data structures used frequently in decision-making models. You must master Binary Trees and Binary Search Trees. Practice writing algorithms for inorder, preorder, and postorder traversals. The 2026 paper evaluates your ability to maintain balance in dynamic trees. Study AVL tree rotations (LL, RR, LR, RL) thoroughly. Expect a ten-mark question asking you to insert a series of integers into an AVL tree and rebalance it step by step.

Non-Linear Structures: Graphs and AI Search

Graphs represent network structures like neural network topologies and state spaces. You must know how to represent graphs using adjacency matrices and adjacency lists. Master Breadth-First Search and Depth-First Search traversals. The paper features numerical or algorithmic questions on finding the Minimum Spanning Tree using Prim and Kruskal algorithms. You must also study shortest path algorithms like Dijkstra's algorithm, which forms the foundation of pathfinding in intelligent agents.

Sorting, Searching, and Hashing

You must memorize the exact code and time complexity for quick sort, merge sort, and heap sort. Examiners often give an array of eight numbers and ask you to show the partition steps for quick sort or the heap creation steps for heap sort. For searching, understand binary search logic and its logarithmic time bounds. Study hashing techniques and collision resolution strategies like chaining, linear probing, and quadratic probing.

Answer Writing Strategy for High Marks

RTU evaluators look for clean syntax, clear dry-run steps, and accurate structural diagrams in your answer booklet. Use a blue pen for your general explanations and a black pen for writing formal code blocks and dry-run tables.

In Part A, answer directly. If the question asks for the worst-case time complexity of binary search, write exactly O(logn) and give the condition of a sorted input array. Keep your answers factual and precise.

In Part B, accompany your text with a structural illustration. When explaining the deletion of a node in a linked list, draw the pointer blocks and show the modification of the next-pointer addresses explicitly.

In Part C, logic execution is essential. When solving a ten-mark sorting or tree insertion question, do not just write the final answer. Draw the complete state of the array or tree after every single step or iteration. If you write a programming function, include brief comments explaining your variable initializations and loop terminating conditions. The university uses step-by-step marking, which ensures you receive partial credit even if a minor syntax error occurs at the end of a long script. Draw a box around your final time complexities and algorithmic outputs.

Time Management During the Exam

Allocate 20 minutes to Part A. Spend 40 minutes on Part B. Reserve the remaining 120 minutes for the three long-answer questions in Part C. Writing full algorithms, tracing graph paths, and drawing multi-step tree operations requires substantial time. This distribution provides you with 40 minutes per major question, giving you ample time to check your logic and verify your loop bounds. Use the final 10 minutes to verify your code syntax, ensure all pointer links in your diagrams are pointed in the correct direction, and check that all question parts are numbered correctly.