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ID1020 Algorithms and Data Structures 7.5 credits

The last opportunity to do exmination in the course (exam and labs) will be in P2 fall semester 2022. The course has been replaced by ID2021 (with a smaller scope). If you are interested in re-examination in ID1020 in P2 contact Robert Rönngren (by mail)

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus ID1020 (Autumn 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Basic algorithm analysis:

  • Simpler analysis with respect to the resource needs of algorithms in the form of time and memory.

Fundamental algorithms:

  • simple numerical algorithms
  • sequential and binary search algorithms
  • Depth first search and Width first search.
  • sorting algorithms: selection sorting, insertion sorting, Quicksort, heapsort, mergesort.

Fundamental data structures:

  • linear lists, stacks, queues, hash tables, binary tree, heaps, binary search trees and problem trees.

Program Design:

  • design and implementation of programmes that use basic algorithms and data structures to solve computer science problems.

Intended learning outcomes

On completion of the course, students should be able to

  • describe a number of common algorithms for search and sorting and their properties
  • compare algorithms with regard to time and memory usage
  • implement data structures as linear lists stacks, queues, hash tables, binary tree and search trees
  • identify problems where the data structures above are useful and design simple algorithms with these
  • write programmes that use algorithms and data structures by means of good programming principles such as systematic tests and abstraction
  • model problems as search problems and implement algorithms for breadth-first-search, depth-first-search or best-first-search

in order to

  • be able to design programmes that solve problems by using commonly occurring algorithms and data structures
  • acquire sufficient prior knowledge to be able to take advanced courses in computer science.

Literature and preparations

Specific prerequisites

Completed course in programming equivalent to ID1018.

Active participation in a course offering where the final examination is not yet reported in LADOK is considered equivalent to completion of the course. This applies only to students who are first-time registered for the prerequisite course offering or have both that and the applied-for course offering in their individual study plan.

Recommended prerequisites

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


  • ARBA - Course work, 4.5 credits, grading scale: P, F
  • TENA - Written exam, 3.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study


Education cycle

First cycle

Add-on studies

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Robert Rönngren

Supplementary information

In this course, the EECS code of honor applies, see: