The curriculum covers topics in algorithms and data structures, such as hashing and graph algorithms. It addresses how to program such algorithms, as well as how to test them, reason about their correctness and analyse their efficiency. It includes a mathematical treatment of big-O notation.
Total contact hours: 33
Private study hours: 117
Total study hours: 150
Main assessment methods
2 programming assessments (15 hours each) (25% each)
2 hour unseen written examination (50%)
Reassessment methods
Like for like.
The Art of Computer Programming. Donald E. Knuth
The Algorithm Design Manual. Steven S. Skiena
Graphs and Applications. Joan Aldous and Robin Wilson
Graphs, Networks and Algorithms. D. Jungnickel
Data Structures and Algorithms in Java 2nd Edition. M.T. Goodrich and R. Tamassia
Algorithms and Data Structures 2nd Edition. Jeffrey H. Kingston x
The Science of Programming. David Gries
See the library reading list for this module (Canterbury)
8. The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
8.1 specify, test, and verify program properties [B3, B4, B5, B7 ,C1]
8.2 analyse the time and space behaviour of simple algorithms [A5, B1, B4, C2, D4];
8.3 use known algorithms to solve programming problems [A2, A4, A5, B4, D3];
8.4 make informed decisions about the most appropriate data structures and algorithms to use when designing software [A2, A4, B1, B4, C2, D3, D4, D5];
9. The intended generic learning outcomes.
On successfully completing the module students will be able to:
9.1 demonstrate an understanding of trade-offs when making design decisions [B1, C2]
9.2 make effective use of existing techniques to solve problems [B4, D3, D5];
9.3 demonstrate an understanding of how programs (can fail to) match a specification [B7, D4]
9.4 analyse and compare solutions to technical problems [B1, B4, C2, D4]
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