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FSF3565 Program Construction in C++ for Scientific Computing 7.5 credits

About course offering

For course offering

Autumn 2024 Start 26 Aug 2024 programme students

Target group

Only PhD

Part of programme

No information inserted


P1 (3.5 hp), P2 (4.0 hp)


26 Aug 2024
13 Jan 2025

Pace of study


Form of study

Normal Daytime

Language of instruction


Course location

KTH Campus

Number of places

Places are not limited

Planned modular schedule


For course offering

Autumn 2024 Start 26 Aug 2024 programme students

Application code



For course offering

Autumn 2024 Start 26 Aug 2024 programme students


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Course coordinator

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Headings with content from the Course syllabus FSF3565 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • Object-oriented programming, basic notions in, and syntax of, C++

  • Objects, classes and its definition, constructors and destructors

  • Operators, operator overloading, polymorphism

  • Basics of abstract classes, inheritance, generic programming

  • Selected components of the C++ standard library

  • Structured and unstructured grids, data structures for their implementation

  • Implementation of numerical methods for partial differential equations

  • Efficient implementation of numerical algorithms

  • Finite difference methods on structured grids.

Intended learning outcomes

The aim of the course consists of providing knowledge how advanced numerical methods and complex algorithms in Scientific Computing can be implemented in C++.

After completion of the course the students can:

  • Construct simple classes for often used mathematical objects;

  • Create abstract classes and define simple template classes;

  • Implement data structures for manipulating realistic geometry and complex grids for numerically solving partial differential equations;

  • Optimize data structures and algorithms in C++ with respect to efficient computations for large-scale problems;

  • Implement finite difference methods on structured grids.

Literature and preparations

Specific prerequisites

A Master degree including at least 45 university credits (hp) in in Mathematics (including differential equations  and numerical analysis) and Computer Science (including programming). Moreover, English B or equivalent is required.

Recommended prerequisites

Advanced course in numerical analysis (SF2520 or equivalent)


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To be announced at least 4 weeks before the course starts.

Examination and completion

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

Grading scale



  • PRO1 - Project work, 3.5 credits, grading scale: P, F
  • TEN1 - Written exam, 4.0 credits, grading scale: P, 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.

Projects reports

Written examination

Other requirements for final grade

Projects reports accepted.

Written examination passed.

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

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Postgraduate course

Postgraduate courses at SCI/Mathematics