Syllabus for Algorithms and Data Structures III

Algoritmer och datastrukturer III

A revised version of the syllabus is available.

  • 5 credits
  • Course code: 1DL481
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Computer Science A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2015-03-12
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2015-04-27
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Spring 2015
  • Entry requirements:

    120 credits, of which at least 30 credits in Mathematics and 45 credits in Computer Science. Algorithms and Data Structures II.

  • Responsible department: Department of Information Technology

Learning outcomes

To pass the course, the student must be able to

  • use advanced standard methods in algorithm theory, such as perfect hashing and integer programming;
  • analyse NP-completeness;
  • use analysis methods in the areas of amortised analysis and randomised algorithms.

Content

Advanced and modern techniques in algorithmics and analysis methods. Advanced standard methods in algorithm theory, such as perfect hashing and integer programming, NP-completeness, analysis methods in the areas of amortised analysis and randomised algorithms. Connections to modern research in the area.

Instruction

Lectures, labs and lessons.

Assessment

Written and oral presentation of assignments, 2 credits, and written exam, 3 credits.

Transitional provisions

The course cannot be included in a degree together with the courses Algorithms and data structures (DV)3/III (1DL104, 1DL113, 1DL030) and Advanced algorithmics (1DL480).

Syllabus Revisions

Reading list

The reading list is missing. For further information, please contact the responsible department.

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