Postgraduate Course: Programming Skills (INFD11016)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course is designed to help you to produce higher quality code; code that is readable, maintainable, usable, correct and efficient in less time and with less effort. These programming skills are applicable to programs in any language and the course is illustrated with examples from C, Python, Fortran, and Java. |
| Course description |
The course covers the following:
- Best practices for scientific computing.
- Introduction to operating systems, compilers and batch systems.
- Writing programs for people, programs that are readable, maintainable, and usable.
- Reviewing code to identify bugs and share expertise.
- Debugging using code browsers and debuggers.
- Managing versions and collaborating using revision control.
- Automating common tasks and building programs using a build tool.
- Automated regression and unit testing to help ensure and maintain program correctness.
- Profiling and performance analysis to identify and improve a program's use of processing and memory resources.
- Security, authentication and authorisation concepts.
- REST application programming interfaces.
- Open source software.
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | Students MUST NOT also be taking
Programming Skills (INFR11177)
|
Other requirements | You must have experience in a programming language e.g. C, C++, Python, FORTRAN or Java. If you're unsure if you have the required level of programming please get in touch with the Course Organiser or your Personal Tutor. You must be familiar with programming concepts including conditionals, loops, arrays and functions. A knowledge of bash shell is highly recommended. No knowledge of parallel programming is required. Some of the above relevant prerequisite material will be made available for self-study, but will not be taught in classes. |
Course Delivery Information
|
| Academic year 2022/23, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 1 |
| Course Start Date |
19/09/2022 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 9,
Online Activities 12,
Feedback/Feedforward Hours 1,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
76 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 100 %.
This is a practical course. The course is assessed by two pieces of coursework. The assessments are:
1. Develop code and automated tests in Python (50%)
2. Measure and report performance of a C code (50%)
No Python or C experience is assumed or expected. Students will be given links to Python resources and a handout on C syntax and how to compile and run C programs. |
| Feedback |
Provided on assessed work within 15 working days of deadlines and through tutorial and discussion sessions. One-to-one appointments can also be arranged for further insight |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand how to build, run and develop software in a Linux/Unix environment
- Evaluate, and write, readable source code
- Analyse code and create unit and regression tests
- Design, implement, analyse and write-up software performance experiments
- Evaluate and apply software development tools including version control systems, code browsers, automated test frameworks and profilers
|
Reading List
LEGANTO List also provided
Wilson G, Aruliah D.A., Brown C.T., Chue Hong N.P., Davis M., et al. 'Best Practices for Scientific Computing'. PLoS Biol 12(1): e1001745. doi:10.1371/journal.pbio.1001745.
Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L. and Teal, T. 'Good enough practices in scientific computing'. PLoS Comput Biol 13(6): e1005510. doi:10.1371/journal.pcbi.1005510.
Sandve G.K., Nekrutenko A., Taylor J., Hovig E. 'Ten Simple Rules for Reproducible Computational Research'. PLoS Comput Biol 9(10): e1003285. doi:10.1371/journal.pcbi.1003285.
Barnes, N. and Jones, D. 'Clear Climate Code: Rewriting Legacy Science Software for Clarity'. IEEE Software 28(6), pp36-42, Nov-Dec 2011. doi:10.1109/MS.2011.113.
Bailey, D.H. 'Twelve Ways to Fool the Masses When Giving Performance Results on Parallel Computers', Supercomputing Review August 1991, pp54-55. Author copy: http://crd-legacy.lbl.gov/~dhbailey/dhbpapers/twelve-ways.pdf.
Bailey, D.H. 'Misleading performance in the supercomputing field', Supercomputing '92 Proceedings of the 1992 ACM/IEEE conference on Supercomputing, pp155-158, November 1992. doi:10.1109/SUPERC.1992.236699.
The following text books are not essential, but one or the other is recommended, if pursuing a career in software development:
McConnell, S. 'Code Complete: A Practical Handbook of Software Construction' (2nd ed.), Microsoft Press, 19 Jun 2004. ISBN-10: 0735619670. ISBN-13: 978-0735619678. Either this or The Pragmatic Programmer below is a good programming best practice book.
Hunt, A. 'The Pragmatic Programmer', Addison Wesley, 20 Oct 1999. ISBN-10: 020161622X, ISBN-13: 978-0201616224. Either this or Code Complete above is a good programming best practice book.
Additional links to other recommended papers, blog posts, articles and online resources are provided. |
Additional Information
| Graduate Attributes and Skills |
Project Management
Organisation
Integration of knowledge
Solution exploration, evaluation, and prioritisation
Programming
Critical Analysis
Scientific/Academic Writing
Ability to analyse and interpret results
Written Communication |
| Special Arrangements |
You must have experience in a programming language e.g. C, C++, Python, FORTRAN or Java. If you're unsure if you have the required level of programming please get in touch with the Course Organiser or your Personal Tutor. You must be familiar with programming concepts including conditionals, loops, arrays and functions. A knowledge of bash shell is highly recommended. No knowledge of parallel programming is required. Some of the above relevant prerequisite material will be made available for self-study, but will not be taught in classes. |
| Keywords | Programming,PS,EPCC,Fortran,C,C++,Python,Java,Debugging,Software,Online |
Contacts
| Course organiser | Ms Bianca Prodan
Tel: (0131 6)50 5343
Email: B.Prodan@epcc.ed.ac.uk |
Course secretary | Mr James Richards
Tel: 90131 6)51 3578
Email: J.Richards@epcc.ed.ac.uk |
|
|
University Homepage