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Algorithms and Complexity
 

Algorithms and Datastructures - Conditional Course
Winter Term 2022/23
Fabian Kuhn

 


Course Description

This lecture revolves around the design and analysis of algorithms. We will discuss the concepts and principles of a selection of the very basic but most commonly used algorithms and datastructures. Topics will include for example: Sorting, searching, hashing, search-trees, (priority-)queues and graphalgorithms (like shortest paths, spanning trees, breadth-first- and depth-first-searches).


Schedule

There will be an introductory session on Wednesday, 19th of Oktober 12:15 - 14:00. The session will take place in presence in Room SR 00 007 (G.-Koehler-Allee 106).

There will be a pre-recorded online lecture combined with an interactive exercise lesson. The interactive session takes places on Wednesdays 12:15 - 14:00 in presence.

The recorded lectures and corresponding slides are available on a separate page. Slides & Recordings


Forum: Zulip

We will offer an instant messaging platform (Zulip) for all students to discuss all topics related to this lecture, where you are free to discuss among yourself or pose questions to us.

Most of the communication will happen over Zulip so it is highly recommended you sign up for Zulip and regularly check for updates.

You must be either inside the eduroam network or be connected to the university network via a VPN to access the Link!


Exam

  • Type of exam: The exam will be oral.
  • Date: to be determined.
  • Time: Each Student will be assigned a time slot. We will contact you with the exact time you should appear.
  • Duration: 30 Minutes.
  • Place: Probably some seminar room in building 106. We will clarify that soon.

Exercises

There will be theoretical and programming exercises, designed to teach you the algorithms and methods discussed in the lecture. Actively participating in the exercises and working through the provided feedback is the best way to prepare for the exam!


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Topic Due (12 pm) Exercise Solution
Sorting 26.10. exercise-01, QuickSort.py solution 01, QuickSort.py
O-Notation 02.11. exercise-02 solution 02
Linear Time Sorting 09.11. exercise 03, BucketSort.py, RadixSort.py, Queue.py, ListElement.py solution 03, BucketSort.py, RadixSort.py
Resolution of Collissions 16.11. exercise 04, HashTable solution 04, HashTable
Hashfunctions 23.11. exercise 05 solution 05
Binary Search Trees 30.11. exercise 06, BST.py, input.txt solution 06, BST
Balanced Trees 07.12 exercise 07 solution 07
Graph Traversal 14.12 exercise 08, AdjacencyList.py, Scheduling.py, dag.txt solution 08, Scheduling.py
Minimum Spanning Trees 21.12 exercise 09, TSP.py, AdjacencyMatrix.py, cities.txt Solution 09, TSP
Shortest Paths 11.01 exercise 10, Maze.py, WeighAdjList.py, maze.txt maze_vis.txt Solution 10, Maze.py, solution.txt
Dynamic Programming 18.01 exercise 11, DP.py, set1.txt, set2.txt, set3.txt solution 11, DP.py
String Matching 25.01 exercise 12, StringMatching, input solution 12, StringMatching
Bonus 01.02 exercise 13, Heap solution 13, Heap

Submission of Exercises

Handing in exercises is voluntary, but we highly recommend doing it. If you want feedback to your solutions, you must submit them by Wednesday, 12 pm.

The submission is simply via Zulip: create a .zip archive containing all of your solution files and send that archive as a private Message to the tutor: Mohsen Al-Zeqri

Programming exercises should be solved using Python and handed in as .py files (inside the .zip file).

Solutions to theoretical exercises can be written in Latex (preferred), Word (or similar text programs) or handwritten scans which must be well readable.


Literature