algorithm design and analysis assignment

• OpenClassroom

CS 161 - Design and Analysis of Algorithms

Prof. tim roughgarden, course description.

Course Overview: Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms and recurrences; greedy algorithms; data structures; dynamic programming; graph algorithms; and randomized algorithms.

Required textbook: Kleinberg and Tardos, Algorithm Design, 2005. We will be covering most of Chapters 4–6, some parts of Chapter 13, and a couple of topics not in the book.

Prerequisites: Introduction to proofs, and discrete mathematics and probability (e.g., CS 103 and Stat116). If you have not taken a probability course, you should expect to do some independent reading during the course on topics including random variables, expectation, conditioning, and basic combinatorics.

1. INTRODUCTION (1/4/2011)

2. basic divide & conquer (1/6/2011), 3. the master method (1/11/2011), 4. linear-time median (1/13/2011) we apologize for the poor audio quality in this video., 5. graph search & dijkstra's algorithm (1/18/2011), 6. connectivity in directed graphs (1/20/2011), 7. introduction to greedy algorithms (1/25/2011), 8. minimum spanning trees (1/27/2011), 9. kruskal's algorithm and union-find (2/1/2011), 10. path compression and clustering (2/3/2011), 11. introduction to randomized algorithms (2/8/2011), 12. quicksort (2/10/2011), 13. hashing (2/15/2011), 14. balanced search trees and skip lists (2/17/2011), 15. introduction to dynamic programming (2/22/2011), 16. sequence alignment (2/24/2011), 17. shortest paths: bellman-ford and floyd-warshall (3/1/2011), 18. np-complete problems (3/3/2011), 19. approximation algorithms (3/8/2011), 20. the wider world of algorithms (3/10/2011).

About Us   |   Contact   |   Privacy Policy    |   FAQ   |  

Design and analysis of algorithms

• Asymptotic complexity, O() notation
• Sorting and search
• Algorithms on graphs: exploration, connectivity, shortest paths, directed acyclic graphs, spanning trees
• Design techniques: divide and conquer, greedy, dynamic programming
• Data structures: heaps, union of disjoint sets, search trees
• Intractability

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout, books and references, instructor bio.

Prof. Madhavan Mukund

Course certificate.

DOWNLOAD APP

SWAYAM SUPPORT

Please choose the SWAYAM National Coordinator for support. * :

We've just released our solutions set for the final project, which also includes statistics and common mistakes. The projects are available for pickup in the Gates building, and electronic submissions should be returned soon. Problem Set Six will also be returned soon.

Thanks for a wonderful quarter, and enjoy the rest of the summer!

The final project goes out today. It's due this Saturday, August 17 at 12:15PM. No late submissions will be accepted! Also remember that unlike on the problem sets, you must work on the project entirely on your own. Good luck!

The algorithm we gave for solving the Longest Increasing Subsequence problem on the "Guide to Dynamic Programming" handout had an error in it (sorry about that!) We've posted a corrected version online.

Problem Set Six goes out today. It's due next Monday, August 12 at 2:15PM. This final problem set of the quarter explores dynamic programming in a variety of contexts.

We've also released a guide to dynamic programming outlining how to structure correctness proofs for DP algorithms.

EDIT: Ooops! There was a small typo in the counterexample to why the greedy algorithm for change making doesn't work. It's now fixed in the online version.

Problem Set Five goes out today. It's due next Monday, August 5 at 2:15PM. This problem set explores greedy algorithms and the proof techniques associated with them. Some problems are standard greedy algorithms, while others show how greedy algorithms can find approximately good solutions to hard problems.

We've also released a guide to greedy algorithms that should give you some extra assistance writing proofs. As you'll see, proving greedy algorithms work correctly can be challenging, and we hope that this handout helps out!

Problem Set Four went out today. It's due next Monday, July 29 at 2:15PM. This problem set is about randomness: expected values, probabilities, and universal hashing all make an appearance here, and by the time you've completed the problem set we hope you'll have a much deeper understanding of just how powerful a tool randomness can be.

We've also released a guide to randomized algorithms that should give you a sense for the level of detail we're looking for in your answers.

Problem Set Three went out today. It's due next Monday, July 22 at 2:15PM. This problem set explores divide-and-conquer algorithms and recurrence relations, and we hope that it will cement your understanding of this algorithmic technique!

We have just posted a handout containing useful mathematical terms and identities . We hope that this handout helps you navigate some of the mathematically trickier parts of the course!

Problem Set Two went out today. It's due next Friday, July 12 at 2:15PM. In this problem set, you'll get to play around with graphs and graph algorithms and will gain experience applying the techniques from the course across a variety of domains.

There was a small bug in Monday's lecture's definition of Ω notation. The constant c must be positive, since otherwise f(n) = Ω(g(n)) for any f and g by just setting c = 0. The slides have been updated to correct for this.

Sorry about that!

Problem Set One went out today. It's due next Wednesday, July 3 at 2:15PM. This problem set explores O, Ω, and Θ notations, algorithm design and correctness, and basic graph algorithms. By the time you're done, we hope that you'll have a much better understanding of how to design and analyze algorithms!

We've also put together a handout containing advice and policies for problem sets . We recommend reading over it before starting the problem set.

Hope this helps!

Welcome to CS161! We've got an exciting quarter ahead of us filled with beautiful algorithms and problem-solving strategies. Over the upcoming weeks, we'll explore a variety of ways to model and solve problems that arise in computer science, biology, operations research, networking, and much more.

In the meantime, feel free to check out the course information handout and syllabus to learn more about what this class is all about, the prerequisites, and the course policies. If you have any questions in the meantime, feel free to email me at [email protected] with questions.

See you soon!

00: Course Information 01: Syllabus 02: Problem Set Advice 05: Math Terms and Identities 07: Guide to Reductions 08: Guide to Divide-and-Conquer 10: Guide to Randomized Algorithms 12: Guide to Greedy Algorithms 14: Guide to Dynamic Programming 15: Final Project

Assignments

Problem Set One    (solutions) Problem Set Two    (solutions) Problem Set Three    (solutions) Problem Set Four    (solutions) Problem Set Five    (solutions) Problem Set Six    (solutions) Final Project    (solutions)

Programming Section

Week 1: Introduction    ( data | code ) Week 2: Graph Search    ( data | code ) Week 3: Divide and Conquer    ( data | code ) Week 4: Randomized Algorithms    ( data | code ) Week 5: Greedy Algorithms    ( data | code ) Week 6: Minimum Spanning Trees    ( data | code ) Week 7: Dynamic Programming    ( data | code ) Week 8: Contest Programming    ( data | code )

Office Hours

Keith (Gates 178):

• Tuesday, 2:15PM - 4:15PM
• Thursday, 2:15PM - 4:15PM

Andy (Clark S250):

• Monday / Wednesday, 4PM - 6PM

Sean (Remote OH):

• Sunday, 1PM - 5PM

Kostas (Gates 460):

• Monday / Wednesday, 6PM - 8PM

Phil (Gates B26A):

• Tuesday / Thursday, 10AM - Noon

Julie (Gates B24A):

• Tuesday / Thursday, 6PM - 8PM

Lecture Videos Gradebook

00: Algorithmic Analysis    Slides (Condensed) 01: Fundamental Graph Algorithms I    Slides (Condensed) 02: Fundamental Graph Algorithms II    Slides (Condensed) 03: Fundamental Graph Algorithms III    Slides (Condensed) 04: Fundamental Graph Algorithms IV    Slides (Condensed) 05: Divide-and-Conquer Algorithms I    Slides (Condensed) 06: Divide-and-Conquer Algorithms II    Slides (Condensed) 07: Divide-and-Conquer Algorithms III    Slides (Condensed) 08: Divide-and-Conquer Algorithms IV    Slides (Condensed) 09: Randomized Algorithms I    Slides (Condensed) 10: Randomized Algorithms II    Slides (Condensed) 11: Randomized Algorithms III    Slides (Condensed) 12: Randomized Algorithms IV    Slides (Condensed) 13: Greedy Algorithms I    Slides (Condensed) 14: Greedy Algorithms II    Slides (Condensed) 15: Greedy Algorithms III    Slides (Condensed) 16: Dynamic Programming I    Slides (Condensed) 17: Dynamic Programming II    Slides (Condensed) 18: Dynamic Programming III    Slides (Condensed) 19: Intractable Problems I    Slides (Condensed) 20: Intractable Problems II    Slides (Condensed) 21: Intractable Problems III    Slides (Condensed) 22: Where to Go from Here    Slides

Navigation Menu

Search code, repositories, users, issues, pull requests..., provide feedback.

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly.

To see all available qualifiers, see our documentation .

design-and-analysis-of-algorithms

Here are 55 public repositories matching this topic..., crypticfate5 / rec-design-and-analysis-of-algorithm-daa-digital-cafe.

Contains solutions and explanations for REC's Design and Analysis of Algorithms (DAA) Digital Cafe.

• Updated Dec 6, 2022

safirmotiwala / MIT-Design-and-Analysis-of-Algorithms

Self made codes of Design and Analysis of Algorithms Lab during my third year of BTech.

• Updated Feb 17, 2020

prashantjagtap2909 / DAA

Practical Assignments and Mini Project of Design and analysis of algorithm.

• Updated Oct 17, 2023

Prago2001 / LP-3

SPPU BE COMP(2019 Pattern) - LP 3 Assignments

• Updated Jun 23, 2023
• Jupyter Notebook

githubhosting / DAA-Lab

Algorithm Lab 4th Sem

• Updated Aug 14, 2023

hamadhassan / Design-and-Analysis-of-Algorithm

Algorithm analysis is an important part of computational complexity theory, which provides theoretical estimation for the required resources of an algorithm to solve a specific computational problem.

• Updated May 17, 2023

bdebo236 / edit-distance

My implementation of Edit Distance problem with Dynamic Programming in full python. Also has a simple GUI with it.

• Updated Nov 4, 2020

santhosh-programmer / CS19341-Design-and-Analysis-of-Algorithms-REC-DigitalCafe

Contains all answers for Rajalakshmi college's Digial cafe CS19341-Design and Analysis of Algorithms. HAPPY CODING !!!

• Updated Dec 5, 2022

vaibhavbichave / LP-I

This repository contains LP-I assignment of SPPU, Third Year IT Syllabus (2019 pattern)

• Updated Nov 30, 2021

dashroshan / daa-oop-lab

📝 3rd semester DAA and OOP lab question solutions in C++

• Updated Aug 3, 2023

GauravJain28 / ADA-Assignments

This repo contains the assignments of the course COL351: Analysis and Design of Algorithms offered in First (Diwali) Sem, 2021-22 at IIT Delhi

• Updated Dec 9, 2021

nixrajput / b-tree-java

B-Tree implementation using Java programming language.

• Updated Jan 1, 2021

Prem-Jain / Data-Structures

Data Structures

• Updated Oct 9, 2022

rohithpala / C

• Updated Aug 11, 2022

neilmehta31 / Bentley_Ottmann_algo_CompGeo

Bentley Ottman Algorithm to find the intersection points in the 2d plane for lines. The algorithm is input sensitive and has a running time complexity of O((N + K) log N) and space complexity of O(N).

• Updated Apr 9, 2022

nabobery / IIITDMK-Codes-Year-2

Codes done by me in Labs, projects and exams in my 2nd Year at IIITDMK

• Updated Apr 23, 2022

prathwik0 / design-and-analysis-algorithms-in-c

Design and Analysis of Algorithms in C

• Updated Jul 23, 2023

ashu1230 / 5TH-SEM

COMPILER DESIGN ,DESIGN AND ANALYSIS OF ALGORITHMS ,DATABASE MANAGEMENT SYSTEM

• Updated Mar 16, 2023

shubh0403 / DAA-Delhi-University-Practicals-Semester-4

These practicals questions are from the guidelines given for semester 4 of BSc(Hons) Computer Science at University of Delhi . The link for Practical files bot is given in the readme file.

• Updated May 6, 2023

PATEL96 / CollegeWork

All codes Done during my Practical Session with Some Amazing Concepts

• Updated Apr 4, 2024

Improve this page

Add a description, image, and links to the design-and-analysis-of-algorithms topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the design-and-analysis-of-algorithms topic, visit your repo's landing page and select "manage topics."

Assistant Professor, Xiamen University

• Google Scholar

CST207 Design and Analysis of Algorithms

Undergraduate course of computer science and technology, Xiamen University Malaysia, 2020-04

This course covers introduction to algorithms, asymptotic analysis, analyzing algorithms, probabilistic analysis, recursive algorithm, divide-and-conquer algorithms, dynamic programming, greedy algorithms, NP-complete theory, backtracking, branch-and-bound, searching problems and approximation algorithms.

Lecture Notes

Lecture 1: Introduction to Algorithms

Lecture 2: Theoretical Analysis

Lecture 3: Probabilistic and Recursive Analysis

Lecture 4: Divide-and-Conquer and Sorting Algorithms 1

Lecture 5: Divide-and-Conquer and Sorting Algorithms 2

Lecture 6: Dynamic Programming

Lecture 7: The Greedy Approach

Lecture 8: Backtracking

Lecture 9: Branch-and-Bound

Lecture 10: The Searching Problem

Lecture 11: The Theory of NP

Lecture 12: Approximation Algorithms

Assignments and Projects

Assignment 1

Assignment 2

Assignment 3

Assignment 4

Assignment 5

Assignment 6

• Interview Q

DAA Tutorial

Asymptotic analysis, analysis of sorting, divide and conquer, lower bound theory, sorting in linear time, binary search trees, red black tree, dynamic programming, greedy algorithm, backtracking, shortest path, all-pairs shortest paths, maximum flow, sorting networks, complexity theory, approximation algo, string matching.

Interview Questions

• Send your Feedback to [email protected]

Help Others, Please Share

Learn Latest Tutorials

Transact-SQL

Reinforcement Learning

R Programming

React Native

Python Design Patterns

Python Pillow

Python Turtle

Preparation

Verbal Ability

Company Questions

Trending Technologies

Artificial Intelligence

Cloud Computing

Data Science

Machine Learning

B.Tech / MCA

Data Structures

Operating System

Computer Network

Compiler Design

Computer Organization

Discrete Mathematics

Ethical Hacking

Computer Graphics

Software Engineering

Web Technology

Cyber Security

C Programming

Control System

Data Mining

Data Warehouse

Browse Course Material

Course info, instructors.

• Prof. Erik Demaine
• Prof. Srini Devadas
• Prof. Nancy Lynch

Departments

• Electrical Engineering and Computer Science
• Mathematics

As Taught In

• Algorithms and Data Structures
• Computer Networks
• Cryptography
• Applied Mathematics

Learning Resource Types

Design and analysis of algorithms, class on design and analysis of algorithms, problem set 1.

This resource contains information regarding class on design and analysis of algorithms, problem set 1.

You are leaving MIT OpenCourseWare

Course Name: Fundamental Algorithms: Design and Analysis

• About Course
• Certificate Type
• Toppers list

Course abstract

This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

Course Instructor

Prof. Sourav Mukhopadhyay

Teaching assistant(s),  course duration : sep-oct 2016,   view course,  syllabus,  enrollment : 30-jul-2016 to 05-aug-2016,  exam registration : 29-jul-2016 to 24-sep-2016,  exam date : 16-oct-2016, 23-oct-2016,   course statistics will be published shortly, certificate eligible, certified category count, successfully completed, participation.

Category : Successfully Completed

Category : Elite

Category : Gold

>=90 - Elite + Gold 60-89 - Elite 40-59 - Successfully Completed <40 - No Certificate

Final Score Calculation Logic

• Assignment Score = Average of best 3 out of 4 assignments.
• Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment score

RITWIK DATTA 92%

TECHNO INDIA, SALT LAKE, WEST BENGAL

SAURAV PANDEY 90%

JSS ACADEMY OF TECHNICAL EDUCATION, NOIDA

SUDIPTA MUKHERJEE 86%

ABHAY KUMAR JHA 85%

KUSHAL KUMAR DEY 85%

HARSH YADAV 85%

PRAMIT BHATTACHARYYA 85%

TATA CONSULTANCY SERVICES LIMITED

JAYANT PRIYADARSHI 85%

HALDIA INSTITUTE OF TECHNOLOGY

AMAN CHOUDHARY 84%

JADAVPUR UNIVERSITY

ASHISH JAISWAL 84%

MANISHA SINHA 84%

PUNIT YOGENDRA MASTER 84%

TATA CONSULTANCY SERVICES

ARUN EDUPUGANTI 83%

PES UNIVERSITY

VR RAGUL 83%

COIMBATORE INSTITUTE OF TECHNOLOGY

ADITYA NARAYAN 82%

DAYANANDA SAGAR UNIVERSITY

TRINA BAKSHI 82%

PRANJALL KUMAR 82%

SIES GRADUATE SCHOOL OF TECHNOLOGY

ROSHAN PAWAR 82%

RADHARAMAN INSTITUTE OF TECHNOLOGY AND SCIENCE

Score Distribution Graph - Legend

Assignment score: distribution of average scores garnered by students per assignment., exam score : distribution of the final exam score of students., final score : distribution of the combined score of assignments and final exam, based on the score logic..