Introductory description
Data structures and algorithms are fundamental to programming and to understand computation. The purpose of this module is to provide students with a coherent introduction to techniques for using data structures and some basic algorithms, and with the tools for applying these techniques to computational problems.
Module aims
Teaching and learning methods include lectures and reading materials which describe algorithmic techniques and applications of these techniques to specific problems. Problem sheets give students opportunities to practice problem solving.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Basics of algorithm analysis.
- Elementary graph algorithms.
- Greedy algorithms.
- Divide-and-conquer algorithms.
- Dynamic programming.
- Network flows.
- NP and computational intractability.
Learning outcomes
By the end of the module, students should be able to:
- Understanding a variety of techniques for designing algorithms and data structures, and ability to use them to solve problems.
- Understand a variety of data structures and be able to use them effectively to use them effectively in design and implementation of algorithms.
- Understand a variety of techniques for designing efficient algorithms, proving their correctness, and analysing their efficiency.
- Understand some fundamental algorithmic problems and algorithms for solving them.
Indicative reading list
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
Subject specific skills
- Designing algorithms
- Using data structures in algorithm design
- Analysing resource requirements and efficiency of algorithms
- Proving correctness of algorithms
Transferable skills
- Critical and creative thinking, problem solving
- Reading, understanding, and writing for mathematics and algorithms
- Written communication: problems, solutions, analysis
Study time
| Type |
Required |
| Lectures |
30 sessions of 1 hour (20%)
|
| Seminars |
9 sessions of 1 hour (6%)
|
| Private study |
111 hours (74%)
|
| Total |
150 hours |
Private study description
- Revising the material covered in the lectures and seminars.
- Reading the recommended textbooks (relevant sections and chapters).
- Attempting the problems from exercise sheets before weekly seminar classes.
- Understanding the feedback given on assessed work and in weekly seminar classes.
- Further problem solving based on revision and self-study exercises posted in the exercise sheets.
- Further problem solving based on textbook content.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Assessment group D3
|
Weighting |
Study time |
Eligible for self-certification |
|
CS260 class test
|
20%
|
|
No
|
|
50 minute class test
|
|
|
Problem Sheet 2
|
5%
|
|
Yes (extension)
|
|
An assessed problem sheet.
This assessment is eligible for self-certification (extension).
No submissions will be accepted beyond five working days after the published deadline.
|
|
|
Problem Sheet 1
|
5%
|
|
Yes (extension)
|
|
An assessed problem sheet.
This assessment is eligible for self-certification (extension).
No submissions will be accepted beyond five working days after the published deadline.
|
|
|
In-person Examination
|
70%
|
|
No
|
|
CS260 exam
- Answerbook Gold (24 page)
|
Assessment group R2
|
Weighting |
Study time |
Eligible for self-certification |
|
In-person Examination - Resit
|
100%
|
|
No
|
|
CS260 resit examination
- Answerbook Gold (24 page)
|
Feedback on assessment
Individual written feedback on each assignment.
Past exam papers for CS260
Courses
This module is Core for:
-
Year 2 of
UCSA-G500 Undergraduate Computer Science
-
UCSA-G503 Undergraduate Computer Science MEng
-
Year 2 of
G500 Computer Science
-
Year 2 of
G503 Computer Science MEng
-
Year 2 of
UCSA-I1N1 Undergraduate Computer Science with Business Studies
-
Year 2 of
USTA-G302 Undergraduate Data Science
-
Year 2 of
USTA-G305 Undergraduate Data Science (MSci) (with Intercalated Year)
-
Year 2 of
UCSA-G4G1 Undergraduate Discrete Mathematics
-
Year 2 of
UCSA-G4G3 Undergraduate Discrete Mathematics
This module is Option list B for:
-
Year 2 of
UMAA-G105 Undergraduate Master of Mathematics (with Intercalated Year)
-
Year 2 of
USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
-
Year 2 of
UMAA-G100 Undergraduate Mathematics (BSc)
-
UMAA-G103 Undergraduate Mathematics (MMath)
-
Year 2 of
G100 Mathematics
-
Year 2 of
G103 Mathematics (MMath)
-
Year 2 of
UMAA-G106 Undergraduate Mathematics (MMath) with Study in Europe
-
Year 2 of
UMAA-G1NC Undergraduate Mathematics and Business Studies
-
Year 2 of
UMAA-G1N2 Undergraduate Mathematics and Business Studies (with Intercalated Year)
-
Year 2 of
UMAA-GL11 Undergraduate Mathematics and Economics
-
Year 2 of
UECA-GL12 Undergraduate Mathematics and Economics (with Intercalated Year)
-
Year 2 of
UMAA-G101 Undergraduate Mathematics with Intercalated Year