Syllabus for Computer Programming II
- 5 credits
- Course code: 1TD722
- Education cycle: First cycle
Main field(s) of study and in-depth level:
Computer Science G1F,
- Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Established: 2007-03-15
- Established by:
- Revised: 2022-02-17
- Revised by: The Faculty Board of Science and Technology
- Applies from: Autumn 2022
Computer Programming I
- 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 software development;
- 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 abstract data types such as stacks, queues, generators and dictionaries;
- describe the underlying principles for exception-based error handling and to be able to use it in programs;
- explain the limitations in Python and ways to integrate Python with other languages;
- implement programs with both sequential and parallel or event-driven flows, including simple parallel processing, and discuss the differences.
Continued programming in Python: polymorphism, duck typing, exceptions. The concepts of stacks, queues, simple graphs such as lists and trees, hash tables, dictionaries in general with Python's Dictionary as a special case. Generators supported by the yield keyword.
Basic algorithms for storage, searching and sorting. Debugging, versioning and testing. Asymptotic time complexity analysis. Characteristics of Python as a language and programming environment compared to C++. Implementation and basic performance comparisons for identical algorithms in Python and C++.
Code represented as objects, including lambda expressions, and the use of such constructs for event-driven and parallel programming in Python.
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.
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The reading list is missing. For further information, please contact the responsible department.