Programming Concepts (G6090A)
Programming Concepts
Module G6090A
Module details for 2025/26.
15 credits
FHEQ Level 4
Module Outline
In this module, apprentices be introduced to algorithmic problem solving. It will answer the following questions: What is a problem specification, an algorithm, a computation? What are their properties? How does one develop an algorithm? How can one rigorously argue that an algorithm computes correct solutions to a given problem? How can one measure the efficiency of an algorithm and the complexity of a problem? For the sake of writing algorithms, a simple algorithmic language (pseudo code) is used.
The focus is on algorithmic thinking. Basic elements of the programming language Python are introduced as means to discuss the differences between programming languages and pseudocode, and between programs and algorithms in particular cases. Apprentices are shown how to go from an algorithm to an implementation, and how to use the interpreter to help them test and design new algorithms.
Finally, the concept of time complexity of an algorithm is presented and asymptotic complexity classes are discussed.
The exercise classes and coursework are based on a series of examples. Apprentices will implement these in Python as a way to reinforce their understanding of program behaviour and give them practice writing simple programs.
Library
D. Harel and Y. Feldman. Algorithmics: The Spirit of Computing. Addison Wesley 2004.
Searching, sorting and other simple (and intuitive) algorithms are specified and developed. Principles like divide-and-conquer and recursive programming will be applied and explained.
Two important properties of algorithms are Correctness and Complexity. Algorithms should only compute correct solutions of a problem. To establish correctness, some relevant (propositional and predicate) logic is introduced in an informal style (focusing on logical reasoning principles rather than logical calculi).
Module learning outcomes
Develop an algorithm from a given problem specification
Prove that a given algorithm is correct for a given problem specification
Analyse a given algorithm and establish its time complexity class
Spot mistakes and suggest possible improvements for a given algorithm
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Project | T1 Week 11 | 50.00% |
| Computer Based Exam | XVAC Week 1 (1 hour) | 50.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Semester | Online Lecture | 2 hours | 10101010100 |
| Autumn Semester | Workshop | 3 hours | 01010101010 |
| Autumn Semester | Online Seminar | 1 hour | 00000000001 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Philip Saville
Assess convenor
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