Undergraduate Programme and Module Handbook 2017-2018 (archived)
Module COMP1081: ALGORITHMS AND DATA STRUCTURES
Department: Computer Science
COMP1081: ALGORITHMS AND DATA STRUCTURES
| Type | Open | Level | 1 | Credits | 20 | Availability | Available in 2017/18 | Module Cap | Location | Durham |
|---|
Prerequisites
- A-level Mathematics Grade A.
Corequisites
- Introduction to Programming OR Computational Thinking
Excluded Combination 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 algorithms.
- Basic string 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/Hours | |
|---|---|---|---|---|---|
| lectures | 44 | 2 per week | 1 hour | 44 | |
| practical classes | 22 | 1 per week | 2 hours | 44 | ■ |
| preparation and reading | 112 | ||||
| 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.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University