Re-exam Results

Written on 21.04.22 by Karl Bringmann

The results of the re-exam are now visible after logging into this course webpage. If you want to inspect your re-exam, please contact Prof. Bringmann.

Algorithms and Data Structures (block course)

The course will cover basic and advanced data structures & algorithms and their analysis. Examples of data structures are cuckoo hashing, splay trees, randomized search trees, union-find structures. In terms of problem domains, we cover graphs, strings, polynomials, and geometry. Furthermore, we discuss algorithm analysis techniques such as amortization and randomization, and general algorithm design principles.

Time & Date & Format

This core course will be offered in an intensive block version between February 28 and March 25. We strongly recommend that you participate in this course being present in the classroom. However, we also make it possible to take the course remotely, see Information->Virtual Guide.

The format of the course will be as follows: A "unit" consists of a 70 minute lecture, followed by 2 hours of group work on an exercise sheet, followed by a short discussion section with a tutor (tutorial). Typically we will have two units a day, the first starting at 9am, the second at 2pm, Monday through Friday, except for all Wednesdays, which will have only the morning unit.

The lecture will usually take place in room HS II in building E2 5. However, on some exceptions we change to different rooms, for details see Information->Timetable or see the list of topics below.

The tutorial will take place at 12:00 and at 17:00 in seminar room 014 in building E1 3. The seminar rooms 014 and 015 in building E1 3 are reserved throughout the whole lecture period as working spaces.

For information how to join the lecture or tutorial virtually, see Information->Virtual Guide.

This will be a very intensive course. Do not plan on doing anything else serious beside it.


Your final grade will be determined by your performance on a midterm exam (35%) and a final exam (65%). There will be a repeat exam for the final. Admittance to the exams requires active participation in the course.

Midterm: 11.3. 14:00-17:00 GHH lecture hall

Endterm: 31.3. 16:30-19:00 GHH lecture hall

Re-Exam: 13.4. 16:00-19:00 HS002 E1 3


The course requires basic knowledge in algorithms and data structures as covered for example by the course "Introduction to Algorithms and Data Structures" ("Grundzüge von Algorithmen und Datenstrukturen"). In particular, you should be familiar with correctness proofs of algorithms. Specific concepts that you should have basic familiarity with and should be able to apply include:

  • pseudocode notation
  • O-notation, running time analysis
  • binary search
  • basic sorting algorithms (e.g. mergesort)
  • arrays, linked lists
  • stacks, queues
  • heaps / priority queues
  • binary search trees, balanced binary search trees (e.g. AVL trees)
  • definition of a graph
  • graph traversal (e.g. depth first search / breadth first search)

In case you want to read up on these topics we recommend the script of the course "Introduction to Algorithms and Data Structures", see Information->Materials.

Tentative List of Topics

  • greedy algorithms
  • dynamic programming
  • divide and conquer (e.g. master theorem, integer multiplication, FFT)
  • randomized algorithms (e.g. quicksort, randomized search trees, hashing)
  • amortization (e.g. Fibonacci heaps, union find)
  • strings (e.g. pattern matching, tries)
  • graphs (e.g. shortest paths, maxflow, matching)
  • (high-dimensional) geometry
Date Lecturer Topic Comment
28.2. 9am RS Intro: machine model, O-notation  
28.2. 2pm RS Divide and Conquer I: basic examples, master theorem  
1.3. 9am RS Divide and Conquer II: Strassen, Karatsuba  
1.3. 2pm RS Divide and Conquer III: Toom-Cook, FFT  
2.3. 9am RS Divide and Conquer IV: applications of FFT  
3.3. 9am KB Randomized I: model, quicksort, rank select room change: HS002 E1 3
3.3. 2pm KB Randomized II: dictionaries, randomized search trees, treaps room change: HS III E2 5
4.3. 9am KB Randomized III: hashing room change: HS002 E1 3
4.3. 2pm KB Randomized IV: more on hashing  
7.3. 9am RS Amortization I: intro room change: HS III E2 5
7.3. 2pm RS Amortization II: Fibonacci heaps / hollow heaps  
8.3- 9am RS Amortization III: splay trees  
8.3. 2pm RS Amortization IV: union find  
9.3. 9am KB Strings I: DP for LCS  
10.3. 9am KB Strings II: string matching: Rabin-Karp, Knuth-Morris-Pratt  
10.3. 2pm KB Strings III: string matching continued, tries  
11.3. 9am KB Strings IV: suffix trees  
11.3. 2pm   Midterm Exam GHH lecture hall
14.3. 9am RS Graphs I: intro, BFS+DFS, Dijkstra  
14.3. 2pm RS Graphs II: shortest path: Bellman-Ford, Floyd-Warshall, Johnson, ...  
15.3. 9am RS Graphs III: more shortest paths  
15.3. 2pm RS Graphs IV: minimum spanning tree  
16.3. 9am KB Graphs V: maxflow: intro, maxflow mincut  
17.3. 9am KB Graphs VI: maxflow: Ford-Fulkerson  
17.3. 2pm KB Graphs VII: maxflow: blocking flows  
18.3. 9am KB Graphs VIII: maximum matching  
18.3. 2pm KB Graphs IX: global mincut  
21.3. 9am RS Geometry I: orthogonal range searching  
21.3. 2pm RS Geometry II: sweep  
22.3. 9am RS Geometry III: point sets viewed globally  
22.3. 2pm RS Geometry IV: point sets viewed locally  
23.3. 9am RS Geometry V: arrangements, duality room change: HS002 E1 3
24.3. 9am KB SAT Algorithms room change: HS001 E1 3
24.3. 2pm KB Teaser: Fine-Grained Complexity  
25.3. 9am KB Teaser: Streaming and Sketching I room change: HS002 E1 3
25.3. 2pm KB Teaser: Streaming and Sketching II  


The course will not follow a particular book. The following is a list of literature that could be useful.

  • [MS] K. Mehlhorn, P. Sanders: Algorithms and Data Structures - The Basic Toolbox, Springer, 2008 (ISBN: 9783540779773)
  • [CLRS] T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms - Second Edition, McGraw-Hill, 2001 (ISBN: 0262531968)
  • [KT] J. Kleinberg and E. Tardos, Algorithm Design, Addison Wesley, 2005 (ISBN: 0-321-29535-8)
  • [Meh] K. Mehlhorn, Data Structures and Algorithms, Vols. 1-3, Springer Verlag, 1984
  • [Koz] D. Kozen, The Design and Analysis of Algorithms, Springer Verlag, 1991
  • [GKP] R. Graham, D. E. Knuth, O. Patashnik, Concrete Mathematics, Addison-Wesley, 1994
  • [CR] M. Crochemore, W. Rytter, Text Algorithms, Oxford University Press, 1994
  • [Sch] A. Schrijver, A Course in Combinatorial Optimization, 2013
  • [BKOS] M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf, Computational Geometry, Springer Verlag, 2000
  • [Eri] J. Erickson, Algorithms, 2019 (Free electronic version)
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