Algorithms and Complexity

Algorithms and Datastructures - Conditional Course
Summer Term 2023
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).


There will be an introductory session on Wednesday, 19th of April at 14:15 in presence in room 051-00-031.

There will be a pre-recorded online lecture combined with an interactive exercise lesson. The interactive session takes places on Wednesdays 14:15 - 16:00 in room 051-00-031.

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!


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!

Topic Due (12 pm) Exercise Solution

Sorting 26.04. exercise-01, QuickSort.py solution 01, QuickSort.py
O-Notation 03.05. exercise-02 solution 02
Linear Time Sorting 10.5. exercise 03, BucketSort.py, RadixSort.py, Queue.py, ListElement.py solution 03, BucketSort.py, RadixSort.py
Resolution of Collissions 17.05. exercise 04, HashTable solution 04, HashTable plot-logscale, plot-linear
Hashfunctions 24.05. exercise 05 solution 05
Binary Search Trees 07.06. exercise 06, BST.py, input.txt solution 06, BST
Balanced Trees 14.6 exercise 07 solution 07
Graph Traversal 21.06 exercise 08, AdjacencyList.py, Scheduling.py, dag.txt solution 08, Scheduling.py
Minimum Spanning Trees 28.06 exercise 09, TSP.py, AdjacencyMatrix.py, cities.txt Solution 09, TSP
Shortest Paths 05.07 exercise 10, Maze.py, WeighAdjList.py, maze.txt maze_vis.txt Solution 10, Maze.py, solution.txt
Dynamic Programming 12.07 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

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.