CUET Computer Science Previous Year Question Paper, Download PDF, Pattern and Tips

Preparing for the Common University Entrance Test (CUET) requires a strategic approach, especially for technically demanding subjects like Computer Science. One of the most effective ways to ensure success is by practicing with the CUET Computer Science Previous Year Question Paper. These papers serve as a blueprint of the actual exam, helping students understand the nuances of the test and identify high-weightage topics.

For candidates aiming to secure a seat in top-tier universities, mastering CUET Computer Science PYQs is non-negotiable. It not only builds conceptual clarity but also enhances time management skills necessary for the 60-minute domain test.

CUET Computer Science Previous Year Question Paper Overview

The CUET exam 2026 is conducted annually by the National Testing Agency (NTA) for undergraduate admissions. For the Computer Science domain (Section II), the paper is designed to test a candidate's proficiency in core computing concepts, primarily based on the NCERT Class 12 syllabus.

CUET Computer Science Previous Year Question Paper Year Wise

Reviewing the CUET Computer Science Previous Year Question Paper Year Wise allows students to track the evolution of the exam difficulty and the shifting focus of the NTA.

Here’s the same information arranged neatly in a clear, easy-to-read table 👇

CUET Computer Science Previous Year Question Paper Pattern

Understanding the CUET Computer Science Previous Year Question Paper Pattern is crucial for effective strategizing. The domain paper is typically divided into sections that cover both general computer science and informatics practices.

Important Topics and Weightage

Based on previous year trends, certain units carry more weight than others:

• Python Programming & File Handling (35-40%): High focus on functions, recursion, and handling text/binary files.

• Database Management System & SQL (20-25%): Covers SQL queries (SELECT, INSERT, Joins), keys, and constraints.

• Computer Networks & Cybersecurity (15-20%): Includes network protocols, topologies, and security threats like viruses or snooping.

• Data Structures & Algorithms (10-15%): Focuses on Stacks, Queues, and searching/sorting algorithms like Bubble and Selection sort.

Benefits of CUET Computer Science Previous Year Question Paper

Solving the CUET Computer Science Previous Year Question Paper provides several advantages that can significantly boost your final score:

• Familiarity with Question Types: Students get accustomed to the variety of MCQs, including assertion-reasoning and condition-based questions.

• Identifies High-Weightage Areas: By analyzing CUET past papers, aspirants can pinpoint recurring themes and prioritize their study schedule accordingly.

• Improves Speed and Accuracy: Practicing in a time-bound manner helps in perfecting the pace required to complete 40 questions in 60 minutes.

• Self-Assessment: It acts as a diagnostic tool to identify weak spots, allowing for targeted revision before the actual exam.

• Reduces Exam Anxiety: Familiarity with the official NTA paper format builds confidence and reduces stress on the exam day.

Tips to Start Preparation with CUET Computer Science PYQs

To make the most of your CUET Computer Science PYQs, follow these strategic steps:

1. Analyze the Syllabus First: Before diving into papers, ensure you have covered the NCERT Class 12 topics as the exam is strictly mapped to this curriculum.

2. Start with Topic-Wise Solving: Instead of a full paper, solve questions related to specific units (like SQL or Python) to strengthen individual foundations.

3. Simulate Exam Conditions: Once the CUET Computer Science syllabus is 70-80% complete, start solving full-length previous year papers using a timer to improve time management.

4. Review Every Mistake: Post-practice analysis is vital. Understand the logic behind incorrect answers to avoid repeating the same errors in the actual CUET test.

5. Focus on Practical Logic: Since over 60% of the paper often covers Python and SQL, practice writing and dry-running code snippets frequently.