# Algorithm Design and Analysis Study Notes for GATE & Computer Science Engineering Exams

By Himanshu Bajpai|Updated : March 25th, 2021

The algorithm subject is very important as it covers all the basic concepts that are used in the Computer Science branch. This subject also carries a good amount of weightage in the GATE exam and all PSU's exams. Also, many questions are asked from this subject in interviews of both the public and private sectors. Here is a list of important topics in this subject. While preparing this subject, we advise you to not miss any of these topics because they are asked for the maximum time in GATE and other exams

Here we are providing the complete study notes on the Analysis of Algorithms for the preparation of the GATE, Computer Science Engineering Exam.

The algorithm subject is very important as it covers all the basic concepts that are used in the Computer Science branch. This subject also carries a good amount of weightage in the GATE exam and all PSU's exams. Also, many questions are asked from this subject in interviews of both public and private sectors. Here is a list of important topics in this subject. While preparing for this subject, we advise you to not miss any of these topics because they are asked for the maximum time in GATE and other exams.
Here we are providing the complete study notes on the Analysis of Algorithms for the preparation of the GATE, Computer Science Engineering Exam.
• Time Complexity
• Properties of Asymptotic Notations
• Comparing functions in terms of Big-Oh
• Finding time complexity of given code snippet
• Divide and Conquer
• Finding minimum/maximum (Recurrence Relation and Time Complexity)
• Power of an element (Recurrence Relation and Time Complexity)
• Binary Search (Recurrence Relation and Time Complexity)
• Merge Sort (Recurrence Relation and Time Complexity)
• Quick Sort (Recurrence Relation and Time Complexity of Best case and Worst-Case)
• Heap Sort (Heap Tree, Heapify function, Recurrence Relation and Time Complexity)
• Greedy Algorithms
• Huffman coding (Finding the average length of the given characters)
• Fractional Knapsack (Finding maximum profit)
• Job sequencing with a deadline (Finding maximum profit to complete given jobs in given deadline)
• Minimum Cost Spanning Tree (Prim's and Kruskal's Algorithm)
• Single Source shortest paths (Dijkstra’s  Algorithms)
• Bellman-Ford Algorithm
• Dynamic Programming
• Longest Common Sub-sequence (Concept with example)
• 0/1 knapsack Algorithms (Concept with example)
• Sum of subset problems (Concept with example)
• Matrix chain Multiplications (Concept with example)
• Hashing
• Collision Resolving Techniques (Open Addressing and Chaining)

Preparing the above topics will cover almost the entire subject which will help you to score maximum marks in this subject.

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