Grades and Inspection II

Written on 12.04.24 by Karl Bringmann

Dear students,

You can now see your grade for the re-exam by logging into the course website.

On Monday from 14:00-15:00 you can inspect your exam in room 415, E1 3.

Algorithms and Data Structures (block course)

The course will cover basic and advanced data structures and algorithms, as well as their analysis. Examples of data structures are perfect 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, and Format

This core course will be offered in an intensive block version between February 28 and March 26. The course can be taken only in presence.

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 Wednesdays, which will have only the morning unit. As an exception, the first lecture happens on February 28 at 14:00. See Information→Timetable for details.

The lecture will take place in room HS003 in building E1 3.

The tutorial will take place at 12:00 and at 17:00 in seminar room 106 in building E1 1. The room 016 in building E1 3 is also reserved throughout the lecture period as working space.

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


You need to register on this webpage to get access to exercise sheets and other course material.


You grade will be determined by a written exam. Admittance to the exams requires active participation in the course.

Endterm:  28.03. 2pm-4pm, HS I in E2 5

Re-Exam:  11.04. 2pm-4pm, HS 002 in 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, 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 videos 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, suffix arrays)
  • graphs (e.g. shortest paths, maxflow, matching)
  • computational geometry
Date Lecturer Topic Comment
28.2. 2pm PW Intro: machine model, O-notation  
29.2. 9am PW Strings I: string matching Morris-Pratt (see [CR])
29.2. 2pm PW Strings II: edit distance and approximate string matching Needleman-Wunsch
1.3. 9am PW Strings III: approximate string matching (cont), suffix array Landau-Vishkin
1.3. 2pm PW Strings IV: suffix array construction, lcp array construction

Kasai et al.

4.3. 9am PW Strings V: lcp array construction (cont), range minimum queries Kasai et al. (cont)
4.3. 2pm PW Advanced Dynamic Programming: LIS, segment trees  
5.3. 9am EK Amortization I: intro  
5.3. 2pm EK Amortization II: Fibonacci heaps  
6.3. 9am EK Amortization III: splay trees  
7.3. 9am EK Amortization IV: union find  
7.3. 2pm KB Randomized I: model, rank select  
8.3. 9am KB Randomized II: randomized search trees  
8.3. 2pm KB Randomized III: hashing  
11.3. 9am KB Randomized IV: more on hashing  
11.3. 2pm KB Randomized V: Monte Carlo algorithms  
12.3. 9am PW Divide and Conquer I: Recurrences (I), Karatsuba  
12.3. 2pm PW Divide and Conquer II: Recurrences(II), Master Theorem, Strassen  
13.3. 9am PW Polynomials I: Introduction  
14.3. 9am PW Polynomials II: FFT  
14.3. 2pm PW Polynomials III: Polynomial division, Schönhage-Strassen  
15.3. 9am EK Graphs I: intro, BFS+DFS, Dijkstra  
15.3. 2pm EK Graphs II: shortest path: Bellman-Ford, Floyd-Warshall, Johnson, ...  
18.3. 9am EK Graphs III: minimum spanning tree  
18.3. 2pm EK Graphs IV: maxflow: intro, maxflow mincut  
19.3. 9am EK Graphs V: maxflow: Ford-Fulkerson  
19.3. 2pm EK Graphs VI: maxflow: blocking flows  
20.3. 9am EK Graphs VII: maximum matching  
21.3. 9am EK Graphs VIII: global mincut  
21.3. 2pm KB Geometry I: intro, convex hull  
22.3. 9am KB Geometry II: convex hull ctd., linear programming  
22.3. 2pm KB Geometry III: orthogonal range searching  
25.3. 9am KB Geometry IV: sweep line, Voronoi diagrams  
25.3. 2pm KB Geometry V: Voronoi diagrams ctd. + intro to models of computation  
26.3. 9am KB Models of Computation: cache hierarchy, IO model  
26.3. 2pm KB Models of Computation: IO model ctd.  


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
  • [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)
  • [CR] M. Chrochemore, W. Rytter, Jewels of Stringology, World Scientific 2002
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