Department of Computer Science | Institute of Theoretical Computer Science

CADMO - Center for Algorithms, Discrete Mathematics and Optimization

Algorithmen und Datenstrukturen 2022

Algorithmen und Datenstrukturen 2022

Fall semester 2022, ETH Zürich

Lecturers: Markus Püschel
David Steurer
Organisation: Tommaso d'Orsi
Jingqiu Ding
Lectures: Thursday, 10:15 - 12:00; 14:15 - 15:00
Exercises: Monday, 9:15 - 12:00

If you have any questions about organisation of the course (NOT related to the content of lectures or exercises), you can send us an email to the following address: Additional information about the course can be found in the course catalogue.

Information for students of the "Computational Biology and Bioinformatics Master" programme.


  • Lectures
  • Exercises
  • Exam information
  • Information about the Moodle forum
  • Announcements



    General information

    The lectures take place on Thursday, 10:15 - 12:00 (in HG F 5, HG F 7); 14:15 - 15:00 (in ETA F 5).

    The lecture will be held physically in the lecture rooms.

    The lectures will not be streamed but will be recorded. The recordings can be found here.

    Lecture notes

    Date Covered topic Notes
    22.09.2022 Introduction.
    • Introduction
    • Grade school multiplication and Karatsuba algorithm
    • Induction
    • O-notation
    Lecture 1
    29.09.2022 Asymptotic notation
    • Star search
    • O-notation
    • Unit-cost random-access model
    Lecture 2
    06.10.2022 Maximum Subarray Sum Problem
    • Naive algorithm, divide-and-conquer algorithm, inductive algorithm
    • Computational complexity of the problem
    Lecture 3
    13.10.2021 Searching algorithms
    • Linear search
    • Interpolation search
    • Binary search
    Sorting algorithms
    • Bubble Sort
    • Selection Sort
    • Insertion Sort
    • The concept of invariants
    Lecture 4
    20.10.2022 Sorting algorithms II
    • Heaps, Heapsort
    • Quicksort
    • Mergesort
    • Lower Bound for Sorting
    Lecture 5
    27.10.2022 Dynamic Programming
    • Longest increasing subsequence
    • Longest common subsequence
    • Edit distance
    Lecture 6
    03.11.2022 Dynamic Programming II
    • Subset Sum problem
    • Knapsack problem
    • Approximation Algorithm for Knapsack
    Lecture 7
    10.11.2022 Data Structures and Abstract Data Types
    • Stacks, Queues
    • Priority Queues
    • Search Trees, AVL Trees
    Lecture 8
    17.11.2022 Graphs
    • Introduction to Graphs
    • Eulerian tours
    Lecture 9
    22.11.2022 Graph algorithms
    • Directed graphs
    • Topological sorting
    • Depth First Search
    Lecture 10
    24.11.2021 Graph algorithms II
    • Depth First Search (continued)
    • Pre-/post-ordering
    • Forward/backwards/cross edges, finding cycles
    • Breadth First Search
    Lecture 11
    01.12.2022 Shortest Paths
    • Shortest Paths
    • Dijkstra's algorithm
    • Bellman-Ford algorithm
    Lecture 12
    07.12.2022 Minimum Spanning Tree
    • Minimum spanning trees
    • Boruvka's algorithm
    • Prim's algorithm
    • Kruskal's algorithm
    Lecture 13
    15.12.2022 Shortest paths 2
    • Floyd-Warshall algorithm
    • Johnson's algorithm
    • Finding number of walks using matrix multiplications
    • Strassen algorithm
    Lecture 14
    22.12.2022 Mediane
    • Auswahlproblem, Mediane
    Lecture 15

    Study and reference material

    Primary study material are the handwritten notes for the individual lectures. You can use the scripts and books as optional reference material, however the presentation of some concepts there might differ significantly from the presentation in class.

    There are several scripts which cover parts of the course. They are additional material, and not per se exam-relevant. You can download the script for algorithms as a PDF-file within the ETH network. Note that the script does not exactly match the course material. In particular, it is more extensive than the course material. For the graph theory part, you can find a script as html or pdf. There is also an older (more extensive, but less adapted to the lecture) script on graph theory here. More additional materials (e.g. old exercises) can also be found on the web page of the previous year.

    For further reading, the book ``Algorithmen und Datenstruktur'', T. Ottmann and P. Widmayer, 6th edition, Spektrum Verlag, 2017, is recommended. You can find it in the ETH Store or download it as a PDF-file within the ETH network. Note, however, that the notions of the book do not always match those of the lecture, e.g. the book uses a different definition of the O notation.

    Additional Literature


    Exercise sheets

    Exercise sheets Solutions
    Exercise Sheet 0 Solutions for sheet 0
    Exercise Sheet 1 Solutions for sheet 1
    Exercise Sheet 2 Solutions for sheet 2
    Exercise Sheet 3 Solutions for sheet 3
    Exercise Sheet 4 Solutions for sheet 4
    Exercise Sheet 5 Solutions for sheet 5
    Exercise Sheet 6 Solution for sheet 6
    Exercise Sheet 7 Solution for sheet 7
    Exercise Sheet 8 Solution for sheet 8
    Exercise Sheet 9 Solution for sheet 9
    Exercise Sheet 10 Solution for sheet 10
    Exercise Sheet 11 Solution for sheet 11
    Exercise Sheet 12 Solution for sheet 12
    Exercise Sheet 13 Solution for sheet 13

    Exercise classes

    The exercise classes take place on Mondays from 9:15 to 12:00.

    Every Monday (starting from 26/09/2022) we will publish a new theory exercise sheet on the webpage, and you have one week to solve the exercises from this sheet.

    The first exercise class takes place on Monday, September 26. It is important to attend since your teaching assistant (TA) will partition you into working groups of 2 (or 3) people. Then you will solve exercises from the current sheet together within the working group. The solutions (one solution per working group) should be handed in at the beginning of the exercise class next Monday (for example, the first exercise sheet is published on September 27, and the solutions should be submitted in the beginning of the exercise class on October 03). The working groups are reassigned every 3 weeks (by the TA).

    During the last hour of the exercise class you will peer-grade the solutions of your fellow students: the TA distributes the solutions among working groups (each working group gets the solution of some other working group), and then asks students to read the solutions and write their comments if they think that they are incorrect or incomplete (comments should contain a clear explanation). After peer grading, you should send your comments to your TA by email.

    All exercise sheets are written in English. You can hand in your solutions either in English or in German. François Hublet and Goran Zuzic are responsible for the content of theoretical exercises. If you have any content-related questions about theory exercises, please send an email to the following address:

    Programming exercises

    A gentle introduction on how to implement algorithms in practice can be found in this webpage (the interactive version can be accessed in Jupyterhub via your ethz account; instructions are given in the webpage). The aim of this document is to show how to translate the high level algorithmic ideas discussed in class into actual Java code. This material is optional and not considered to be part of the course (notice that the programming exercises on Code Expert are part of the course). If needed, you can find an introduction to programming in Java at this link (this material is optional and not considered part of the course).

    The online judging system for programming exercises is Code Expert ( You can get enrolled using this link. You have two warm-up exercises in the Code Expert website to test the environment. These warm-up exercises do not give any bonus point. This pdf explains how to complete one warm-up exercise. More detailed information about the Code Expert system, can be found in the on-line documentation.

    For each set of programming exercises you will have two weeks to submit your solution. The first programming exercise will be published a few weeks after the semester starts.

    Programming exercises are created by Tommaso Pegolotti and Rares Darius Buhai. They are NOT related to the exercise classes and your TAs are not supposed to answer any questions about programming exercises. Questions regarding programming exercises can and should be submitted through the messaging system of Code Expert. This will be the only way of asking questions during the computer part of the exam. We also remark that there is a Moodle Forum in which you can discuss the programming exercises.


    Bonus points

    During the semester, the students can get bonus points for

  • solving the designated parts of the theoretical exercise sheets (in working groups);
  • peer grading the specified part of the theory sheets during the class (in working groups);
  • solving the programming problems (individually).
  • At the end of the term, the bonus points are translated into a bonus grade between 0 and 0.25. The final grade is then the sum of the exam grade and the bonus grade (rounded and capped at 6.0). The students already get the maximal bonus grade (0.25) for 80% of the bonus points. This compensates for possible absences, e.g. due to illness or military service. That is, the formula for the bonus grade is min(0.25, 0.25 * n_points / (0.8 * max_points)), where n_points is your number of bonus points, and max_points is the maximal possible number of bonus points.

    Participation in the bonus system is voluntary. It is possible to get a 6.0 without participating in the bonus system.

    Peer graded solutions must be submitted by the peer graders no later than 23:59 on the same day of the exercise class.

    Rules and integrity

    Each working group must hand in their own, independent solution of the theory exercises. Likewise, programming exercises must be handed in with self-written code. We recommend solving all tasks without the help of external sources (books, internet, solutions from fellow students), as otherwise the learning effect of the tasks is largely lost. Even if you seek advice from an outside source, plagiarism (partial or complete) is not allowed. In this case, we recommend that you put this source aside after reading it and then formulate your solution (on your own!) the next day. Correspondingly, copying third-party code (in whole or in part, also from the Internet) to solve programming tasks is not permitted. The regulation on external sources also applies here by analogy. You are of course allowed to use Java documentation when programming, and in particular to search for syntax. You are not allowed to make your own solutions (whether theory or programming) available for copying. In case of copying, both involved working groups/students lose their points, regardless of whose solution was the original. Moreover, it can lead to further consequences for both working groups/students.

    Exam information

    The exam takes place in the exam session. It consists of two parts, a written theory part and a programming part.

    The exercises (theoretical and programming) that we suggest you to solve during the semester are designed to optimally prepare for the exam.

    You can find a list of some exams from previous years here.

    Technical details on the written exam like allowed aids can be found here. More information will be sent by email in the weeks before the exam.

    Further details will be provided later, additional information relevant for the exam can be found in the course catalogue.

    Exam solution can now be found here.


    The Moodle-Forum is supposed to be used for discussions among the students, but we will check the forum at least twice a week to ensure that it does not contain wrong information. Please follow the following no-spoiler policy: If your answer directly or indirectly contains tips or solution hints for an exercise, then put a clear spoiler warning at the beginning of your post and write the critical part of the post (the possible Spoiler) in white text color. In this way, you enable your fellow students to solve the tasks independently, without accidentally reading your post or the possible hints. Please provide your fellow students with a spoiler-free learning environment by following a corresponding policy in private communication channels (Telegram groups etc.)!

    Formulated solutions (partial or complete) must not be published in the forum or in a Telegram group! This applies to both theory and programming tasks.

    Important note for students of the "Computational Biology and Bioinformatics Master" programme: If your study administration has made the course "Data Structures and Algorithms" mandatory, you will not be able to participate in this course. Instead, you must take the course Nr. 252-0002-AAL. Further information can be found in the course catalogue.