Syllabus for Algorithms and Data Structures I

Algoritmer och datastrukturer I

Syllabus

  • 5 credits
  • Course code: 1DL210
  • Education cycle: First cycle
  • Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F

    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: 2007-03-19
  • Established by:
  • Revised: 2021-11-11
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2022
  • Entry requirements:

    10 credits in computer programming (Program Design, Programming Techniques II, or the equivalent) and 10 credits in mathematics, including basic algebra. Alternatively 45 credits in the Master's Programme in Language Technology (HSP2M).

  • Responsible department: Department of Information Technology

Learning outcomes

On completion of the course, the student should be able to:

  • analyse the runtime performance of a (simple) algorithm/program in terms of the size of its inputs, and this in the average, best, and worst cases.
  • choose appropriate algorithms and data structures for storing data, searching and sorting, as well as implement those algorithms.
  • use and implement basic graph algorithms.

Content

Mathematical foundations: asymptotic notation, summations, recurrence relations.

Data structures: trees, FIFO queue, stack, priority queues, heaps.

Searching: binary search trees, balanced search trees, hash tables.

Sorting: insertion sort, merge sort, quick sort, heap sort.

Graph algorithms: depth first and breadth first search, topological sort and (strongly) connected components.

Design techniques: divide-and-conquer.

Implementation of algorithms and data structures.

Instruction

Lectures, laboratory work, lessons, and mandatory assignments.

Assessment

Written exam (4 p). Assignments (1 p).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Other directives

The unit cannot be included in a degree with Program Design II (1IT022), nor with Data Structures (1DL009, 1TD191, 1MB026).

Syllabus Revisions

Reading list

Reading list

Applies from: Autumn 2022

Some titles may be available electronically through the University library.

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