Algorithms and Datastructures (DAT200)
The course provides an in-depth introduction to some commonly used data structures and algorithms.
Course description for study year 2025-2026
Course code
DAT200
Version
1
Credits (ECTS)
10
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
Admission requirements
Higher engineering education (HING)
Content
Algorithm efficiency analysis. Definition, usage, and implementations of abstract data types: Stacks, queues, lists, associative arrays (dictionary in Python), tree structures, graphs, priority queues, heaps. Hash techniques. Tree structures. Implementation and use of data structures that can represent graphs. Algorithms for sorting and searching. Some basic algorithms for graphs, including wayfinding. Use of recursion as programming technique.
Learning outcome
After ending this course the student should know how to:
Knowledge
Know how basic algorithms for sorting, searching and wayfinding in graphs work.
Know how basic data structures for lists, stacks, queues, priority queues, sets, associative arrays and graphs work
Skills
Be able to calculate the efficiency of algorithms
Be able to implement efficient recursive algorithms
Be able to implement efficient algorithms for sorting and searching
General competency
Know how data structures and algorithms for lists, queues, stacks, heaps, binary trees and graphs can be implemented.
Be able to use standard algorithms and data structures to implement efficient programs
Required prerequisite knowledge
The student is expected to know how to program at a level equivalent to DAT110 or DAT120 Introduction to programming.
Recommended prerequisites
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Written exam | 1/1 | 4 Hours | Letter grades | None permitted |
This course has digital exam. It will be possible to use Scantron to scan drawings made by hand and connect these to the digital exam.
Coursework requirements
There are nine exercises in this course. In order to be allowed to take the exam at least seven out of the nine exercises need to be approved within the given deadline.
Completion of mandatory exercises are to be made at the times and in the groups that are assigned and published. Absence due to illness or for other reasons must be communicated as soon as possible to the laboratory personnel. One cannot expect that provisions for completion of the exercises at other times are made unless prior arrangements with the laboratory personnel have been agreed upon.
Failure to complete the assigned exercises on time or not having them approved will result in barring from taking the exam of the course.
Course teacher(s)
Course coordinator:
Mina FarmanbarHead of Department:
Tom RyenMethod of work
Four hours of lecturing per week. All students can get help for the exercises at a room reserved for the purpose four hours a week. The exercises are approved by presenting them to the teacher or a student assistant during these four hours.
Overlapping courses
| Course | Reduction (SP) |
|---|---|
| Data structures and algoritms (TE0458_1) | 6 |
| Data structures and algoritms (TE0458_A) | 6 |
| Datastructures and algorithms (BIE270_1) | 10 |
