Syllabus for Computer Programming II

Programmeringsteknik II

  • 5 credits
  • Course code: 1TD722
  • 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: 2007-03-15
  • Established by:
  • Revised: 2020-02-10
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 28, 2020
  • Entry requirements: Computer Programming I or the equivalent.
  • Responsible department: Department of Information Technology

Learning outcomes

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

  • use the programming language Python, and tools for testing, debugging and version control, both writing codeand explaining what a given code does;
  • explain the concepts polymorphism and duck typing in Python, and use these concepts in the softwaredevelopment;
  • implement recursive solutions to problems;
  • describe the principle for analysing algorithm efficiency and perform analysis on basic algorithms;
  • describe, implement and use the fundamental data structures lists, hash tables and trees and implement abstractdata types such as stacks, queues, generators and mapping;
  • describe how debugging with exceptions is working and to be able to use it in programs;
  • implement programs with both sequential and event driven flows, incuding simple parallel processing, and discussthe differences.

Content

Continued programming in Python: polymorphism, duck typing, exceptions. The concepts stacks and queues, simplegraphs such as lists and trees, hash tables, mapping in general and Pythons dictionary as a special case. Generators andthe Python yield statement.
Fundamental algorithms for storing, searching and sorting. Debugging, version control and testing. Analysis of asymptotictime complexity.
Python language and programming environment properties compared with C++ . Implemented and basic performancecomparisons between Python and C++ .
Represenation of code as object and lambda expressions, and using this for event driven and parallel programming inPython.

Instruction

Lectures, problem classes/computer lab and compulsory assignments.

Assessment

Written examination (2 credits) and approved assignments (3 credits).

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

Reading list

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