Understanding Polynomial Time Reductions — KopHub

Chapters

On this page & study actions

Assessed progress

Sign in and complete the verified MCQs to track mastery.

Practice this topic Next topicNP-Completeness: Definition and Examples

Home/Sem 3/← Advanced Data Structures/Complexity classes P & NPComplete/Understanding Polynomial Time Reductions

Unit 6: Complexity Classes8 min read

Understanding Polynomial Time Reductions

Assessed progress

Sign in and complete the verified MCQs to track mastery.

Practice this topic Next topicNP-Completeness: Definition and Examples

Practice this subject

Continue to KopHub’s existing question and assessment experience.

PreviousIntroduction to P and NP Classes Next NP-Completeness: Definition and Examples

Advanced Data Structures

6 Modules

Introduction to Algorithms and Pseudocode Recursive Algorithms Performance Analysis: Space and Time Complexity Asymptotic Notations Recurrence Relations and Solving Methods

Algorithmic Paradigms and Divide-and-Conquer Overview Binary Search Algorithm Finding Maximum and Minimum Elements Merge Sort Algorithm Quick Sort Algorithm

Binary Tree Fundamentals Advanced Tree Structures: BSTs, AVL, and Heaps Graph Definitions, Representations, and Traversals Minimum Spanning Tree Algorithms Shortest Path Algorithms

Content unavailableSoon

Greedy Method: General Principles and Machine Scheduling Greedy Method: Knapsack, Job Sequencing, and Optimal Storage Greedy Method: Optimal Merge Patterns and Huffman Codes Dynamic Programming: General Principles and Multistage Graphs Dynamic Programming: Knapsack, TSP, and Optimal Binary Search Trees

Introduction to P and NP Classes Understanding Polynomial Time Reductions NP-Completeness: Definition and Examples NP-Hardness and its Relationship with NP-CompletenessSoon

CSE/SY Sem 3

Leaderboard Calendar Playground

CSE/SY Sem 3

Leaderboard Class Schedule Code Playground Settings

Appearance

Advanced Data Structures

6 Modules

Introduction to Algorithms and Pseudocode Recursive Algorithms Performance Analysis: Space and Time Complexity Asymptotic Notations Recurrence Relations and Solving Methods

Algorithmic Paradigms and Divide-and-Conquer Overview Binary Search Algorithm Finding Maximum and Minimum Elements Merge Sort Algorithm Quick Sort Algorithm

Binary Tree Fundamentals Advanced Tree Structures: BSTs, AVL, and Heaps Graph Definitions, Representations, and Traversals Minimum Spanning Tree Algorithms Shortest Path Algorithms

Content unavailableSoon

Greedy Method: General Principles and Machine Scheduling Greedy Method: Knapsack, Job Sequencing, and Optimal Storage Greedy Method: Optimal Merge Patterns and Huffman Codes Dynamic Programming: General Principles and Multistage Graphs Dynamic Programming: Knapsack, TSP, and Optimal Binary Search Trees

Introduction to P and NP Classes Understanding Polynomial Time Reductions NP-Completeness: Definition and Examples NP-Hardness and its Relationship with NP-CompletenessSoon

DM ADS DT CN SPM COI

MDM ElectiveMDM

Labs & ProjectsLabs