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Algorithms and Datastructures

This is the study programme for 2019/2020. It is subject to change.

The course provides an in-depth introduction to some commonly used data structures and algorithms.

Learning outcome

After ending this course the student should know how to:
  • 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

  • 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


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.

Required prerequisite knowledge


Recommended previous knowledge

DAT100 Object-oriented Programming, DAT110 Introduction to programming


Weight Duration Marks Aid
Written exam1/14 hoursA - FNone permitted

Coursework requirements

Hand-in assignments
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.

Course teacher(s)

Course coordinator
Erlend Tøssebro
Head of Department
Tom Ryen

Method of work

Six 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.
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.

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

Open to

Bachelor studies at the Faculty of Science and Technology.

Master studies at the Faculty of Science and Technology.

Course assessment

Form and/or discussion.


There are many textbooks on algorithms. These textbooks have different levels of complexity and use different programming languages to teach algorithms. This course does not follow any particular textbook but has a curriculum list, including a compendium. The curriculum list and compendium will be posted on Canvas. This course will use the Python programming language to demonstrate the algorithms.
One possible textbook that is on-line is this:
Problem Solving with Algorithms and Data Structures using Python by Brad Miller and David Ranum, Luther College
Alternative textbooks:
- Introduction to Algorithms, 3. edition, by Cormen, Leiserson, Rivest, Stein, MIT press. This textbook is thorough and is used for the master course DAT600 algorithm theory. It is also used in other universities for bachelor courses on algorithms. However, this book is very theoretical and mathematical. All algorithms are illustrated with pseudocode alone and not in a real programming language.
- Python Algorithms: Mastering Basic Algorithms in the Python Language 2nd ed. Edition by Magnus Lie Hetland. Apress. This book covers a slightly different curriculum than DAT200 does.

This is the study programme for 2019/2020. It is subject to change.

Sist oppdatert: 13.11.2019