Search course

Use the search function to find more information about the study programmes and courses available at Chalmers. When there is a course homepage, a house symbol is shown that leads to this page.

Graduate courses

Departments' graduate courses for PhD-students.

​​​​
​​

Syllabus for

Academic year
DAT037 - Data structures
 
Syllabus adopted 2016-01-27 by Head of Programme (or corresponding)
Owner: TKDAT
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: First-cycle
Major subject: Computer Science and Engineering, Information Technology
Department: 37 - COMPUTER SCIENCE AND ENGINEERING


Teaching language: Swedish

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0114 Laboratory 3,0c Grading: UG   3,0c    
0214 Examination 4,5c Grading: TH   4,5c   11 Jan 2017 pm M,  11 Apr 2017 pm M,  17 Aug 2017 am M

In programs

TKTEM ENGINEERING MATHEMATICS, Year 3 (compulsory)
TKAUT AUTOMATION AND MECHATRONICS ENGINEERING, Year 3 (elective)
TKDAT COMPUTER SCIENCE AND ENGINEERING, Year 2 (compulsory)

Examiner:

Docent  Nils Anders Danielsson


Replaces

DAT035   Data structures DAT036   Data structures


  Go to Course Homepage

Eligibility:

In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.

Course specific prerequisites

Programming using object-oriented language (preferably Java). Basic mathematical concepts like sets, functions, relations, graphs, logarithms and proofs by induction.

Aim

To learn about common abstract data types, data structures and algorithms.

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

  • understand and use some basic abstract data types and data structures, including lists, queues, tables, trees and graphs.
  • understand and use some of the algorithms used to manipulate and query basic data structures in an efficient way, and understand why they are correct.
  • analyse the efficiency of (some) algorithms.
  • make informed choices between different data structures and algorithms for different applications.
  • implement abstract data types as interfaces, and data structures as classes, in an object-oriented programming language.

Content

Abstract data types. Simple complexity analysis. Common data structures such as arrays, lists, trees, hash tables and how these can be used to implement abstract data types such as stacks, queues, priority queues, dictionaries and graphs. Standard algorithms for these data structures and their resource demands. Iterators. Sorting algorithms. Standard libraries for data structures and algorithms.

Organisation

Lectures, tutorials and programming assignments.

Literature

See the course web page.

Examination

Invigilated written exam and compulsory programming assignments.


Page manager Published: Thu 04 Feb 2021.