Module Search

COMP1081: ALGORITHMS AND DATA STRUCTURES

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type	Open
Level	1
Credits	20
Availability	Available in 2023/24
Module Cap
Location	Durham
Department	Computer Science

Prerequisites

A-level Mathematics Grade A.

Corequisites

COMP1051 Computational Thinking

Excluded Combinations of Modules

None

Aims

To introduce the theory and practice of problem solving in computing through the development of algorithms, and their associated data structures, for common computer science problems.

Content

Machine models.
Pseudocode and control flow structures.
Basic data structures.
Paradigms and techniques.
Analysis of algorithms.
Basic sorting and searching algorithms.
Basic graph theory and graph algorithms.

Learning Outcomes

Subject-specific Knowledge:

On completion of the module, students will be able to demonstrate:
a knowledge of common data structures and their relative advantages and disadvantages
familiarity with common algorithmic techniques
an appreciation and knowledge of asymptotic notation.

Subject-specific Skills:

On completion of the module, students will be able to demonstrate:
an ability to implement and use common data structures
an ability to select, apply and analyse algorithms.

Key Skills:

On completion of the module, students will be able to demonstrate:
the acquisition of a wide range of problem-solving skills
a facility to apply numeric and systematic reasoning to problem-solving.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Lectures enable the students to learn new material relevant to algorithms and their data structures.
Problem classes enable the students to put into practice learning from lectures and strengthen their understanding through application; in particular, thorugh the implementation of algorithms.
Students are assessed by formative and summative assessment and examinations.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total	Monitored
lectures	44	2 per week	1 hour	44
practical classes	21	1 per week	2 hours	42	Yes
preparation and reading				114
total				200

Summative Assessment

Component: Examination		Component Weighting: 66%
Element	Length / Duration	Element Weighting	Resit Opportunity
Examination	2 hours	100	Yes

Component: Coursework		Component Weighting: 34%
Element	Length / Duration	Element Weighting	Resit Opportunity
Practical work		100	Yes

Formative Assessment

Example formative exercises are given during the course. Additional revison lectures are given in the module's lecture slots in the 3rd term.

More information

If you have a question about Durham's modular degree programmes, please visit our FAQ webpages, Help page or our glossary of terms. If you have a question about modular programmes that is not covered by the FAQ, or a query about the on-line Undergraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.