COM5113 - Algorithms and Data Structures

Objectives:

Assessment tasks are designed to enable students to demonstrate the Learning and Employability outcomes for the relevant level of study. Level Learning Outcomes are embedded in the assessment task(s) at that level. This enables a more integrated view of overall student performance at each level.

Content:

This module incorporates computational thinking as fundamental problem-solving expertise within the realm of core computer science knowledge, expected of and utilised by all computing practitioners. Students are taught core algorithms and data structures and introduced to algorithm analysis and basic computability. They also study data types such as stacks, queues, trees and graphs, understand time and space complexity, write and explain commonly used algorithms, use a variety of different data structures and understand the concepts of computability and complexity.

This involves delving into the computational facets of data representation and fostering familiarity with established, proven solutions to recurring problems encountered in various computing contexts and practical applications.

Learning and Teaching Information:

Workshops
Hours: 60
Intended Group Size: Cohort

Guided independent study
Hours: 240

Further Details Relating to Assessment

Assessment tasks are designed to measure the extent to which you have satisfied the Level Learning Outcomes for your programme. Some modules, for example where there are professional body (PSRB) requirements, will also test for module-specific skills and knowledge.

Algorithm Artefact: This assessment is a practical piece of work with accompanying documentation, where students have to design and implement an algorithm and document the process.

Algorithm Troubleshooting: Students are tasked with undertaking a comprehensive troubleshooting exercise applied to a given scenario.

In computer science classes, formative assessment serves to bolster the skills essential for module success. This includes engaging in practical labs, undertaking design and modelling tasks, delivering case study presentations, completing short quizzes and conducting specific investigation tasks. The provision of formative feedback is integrated seamlessly into class sessions, ensuring an ongoing and iterative process to enhance learning outcomes.

Further details of assessment are available in the Assessment Handbook for your programme and in Assessment Briefs provided by Module Tutors.

Assessment:

001 Algorithm Artefact; 1800 word equiv; end of sem 1 60%
002 Algorithm trouble-shooting; 1200 word equiv.; end of sem 1 40%

Fact File

Module Coordinator - PRS_CODE=
Level - 5
Credit Value - 30
Pre-Requisites - NONE
Semester(s) Offered - 5S1

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