Syllabus for Computer Programming II
A revised version of the syllabus is available.
- 5 credits
- Course code: 1TD722
- Education cycle: First cycle
Main field(s) of study and in-depth level:
Computer Science 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:
- 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
- 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: Autumn 2020
Computer Programming I or the equivalent.
- Responsible department: Department of Information Technology
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.
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.
Lectures, problem classes/computer lab and compulsory assignments.
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.
- Latest syllabus (applies from Autumn 2022)
- Previous syllabus (applies from Autumn 2020)
- Previous syllabus (applies from Autumn 2019)
- Previous syllabus (applies from Autumn 2017)
- Previous syllabus (applies from Spring 2013)
- Previous syllabus (applies from Autumn 2010)
- Previous syllabus (applies from Autumn 2009)
- Previous syllabus (applies from Autumn 2007)
The reading list is missing. For further information, please contact the responsible department.