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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
DAT038 - Data structures and algorithms  
Datastrukturer och algoritmer
Syllabus adopted 2019-02-07 by Head of Programme (or corresponding)
Owner: TKDAT
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: First-cycle
Major subject: Computer Science and Engineering, Software Engineering

The course is full. For waiting list, please contact the director of studies:
Teaching language: English
Application code: 49113
Open for exchange students: No
Maximum participants: 165

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0119 Laboratory 3,0c Grading: UG   3,0c    
0219 Examination 4,5c Grading: TH   4,5c   14 Jan 2021 pm J   07 Apr 2021 pm J,  27 Aug 2021 pm J  

In programs



Peter Ljunglöf

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General entry requirements for bachelor's level (first cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

The same as for the programme that owns the course.
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

Programming in an object-oriented programming language, including recursive functions and methods. Basic mathematical concepts, such as sets, functions, relations, graphs, logarithms and proofs by induction.


Data structures and algorithms are fundamental building blocks in almost all software products. Knowledge of data abstraction, data structures, and algorithms is important in the construction, use, and maintenance of adaptable, reusable, and efficient program components.

The course gives knowledge and skills in the construction and use of data structures and algorithmic concepts, and gives an introduction to algorithm analysis and data abstraction.

Learning outcomes (after completion of the course the student should be able to)

Knowledge and understanding

  • explain some basic abstract data types and data structures, including lists, queues, hash tables, trees and graphs
  • explain some of the algorithms used to manipulate and query these data structures in an efficient way, and explain why they are correct

Competence and skills

  • apply basic abstract data types and data structures, and algorithms related to these
  • implement and use abstract data types as interfaces and data structures as classes, in an object-oriented programming language
  • use a standard library of data structures and algorithms

Judgement and approach

  • analyse the efficiency of different algorithms, for example searching and sorting algorithms
  • make informed choices between different data structures and algorithms for different applications


The course covers the following topics:
  • abstract data types
  • asymptotic efficiency and simple complexity analysis of imperative code
  • common data structures such as arrays, lists, trees, and hash tables 
  • how these can be used to implement abstract data types such as stacks, queues, priority queues, maps, sets, and graphs
  • standard algorithms for these data structures, including their resource demands
  • searching and sorting algorithms
  • standard libraries for data structures and algorithms
  • common algorithm design techniques, such as brute force, divide and conquer, and randomization


The teaching consists of lectures, exercises, and laborations, as well as supervision in connection to the laborations.


See course homepage.

Examination including compulsory elements

The course is examined by an individual written exam given in an examination hall (4.5 hec) and laboratory work (3.0 hec). The laboratory work is normally done in pairs.

Page manager Published: Thu 04 Feb 2021.