410241: Design and Analysis of Algorithms (DAA)

This repository contains valuable resources for the Design and Analysis of Algorithms course under the SPPU Computer Engineering syllabus (2019 pattern). It includes codes, handouts, notes, previous year questions (PYQs), and write-ups for assignments. The materials focus on developing problem-solving abilities, applying algorithmic strategies, analyzing performance, and creating efficient algorithms. Students will explore algorithmic examples in distributed and concurrent environments, enhancing their understanding of multithreaded and distributed algorithms.


Index

Notes

Codes

  1. Code-A1 - Fibonacci Series

Practical

Question Papers


Miscellaneous

-> Disclaimer: Please read the DISCLAIMER file for important information regarding the contents of this repository.

-> Note: Content such as codes, softcopies, write-ups and question papers is provided by us, i.e. our contributors. You are free to use this content however you wish, without any restrictions. Some of the notes and handouts have been provided by our professors, thus to use them for anything other than educational purposes, please contact them.

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-> Motto:

Making information freely accessible to everyone.

-> Keywords:

SPPU, Savitribai Phule Pune University, Pune University, Computer Engineering, COMP, Fourth Year, Final Year, BE, Semester 7, SEM-7, Notes, Codes, Practical work, Handouts, Assignments, PYQs, Design and Analysis of Algorithms, DAA, Problem Solving, Algorithmic Strategies, Performance Analysis, Time Efficiency, Space Efficiency, Distributed Algorithms, Concurrent Algorithms, Multithreaded Algorithms, Asymptotic Performance, Scheduling Algorithms, Sorting Algorithms, Optimal Solutions,


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Description
This repository contains valuable resources for the Design and Analysis of Algorithms course under the SPPU Computer Engineering syllabus (2019 pattern). It includes codes, handouts, notes, previous year questions (PYQs), and write-ups for assignments. The materials focus on developing problem-solving abilities, applying algorithmic strategies, analyzing performance, and creating efficient algorithms. Students will explore algorithmic examples in distributed and concurrent environments, enhancing their understanding of multithreaded and distributed algorithms.
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Python 27.1%