## CE204-5-AT-CA:Data Structures and Algorithms

The details
2024/25
Computer Science and Electronic Engineering (School of)
Colchester Campus & Apprenticeship Location
Autumn Special
Current
Thursday 03 October 2024
Friday 13 December 2024
15
27 June 2024

Requisites for this module
(none)
(none)
(none)
(none)

(none)

(none)

## Module description

Data structures and algorithms lie at the heart of Computer Science as they are the basis for the efficient solution of programming tasks. In this module, students will study core algorithms and data structures, as well as being given an introduction to algorithm analysis and basic computability.

The module will give students core algorithmic skills that are required for Years 2 and 3 of the Computer Science degree schemes.

## Module aims

The aims of this module are to study core algorithms and data structures, as well as an introduction to algorithm analysis and basic computability. Students will study data types such as stacks, queues, trees and graphs, make efficient use of core data types in Java, 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.

## Module learning outcomes

After completing this module, students will be expected to be able to:

1. Demonstrate an understanding of core data types such as stacks, queues, trees, and graphs.
2. Implement core data types in Java and write programs that make efficient use of them.
3. Reason about the time and space complexity of programs.
4. Demonstrate knowledge of commonly used algorithms.
5. Make informed decisions about the choice of data structure or algorithm for solving a problem.
6. Explain the main concepts of computability and how some problems have no algorithmic solution.

## Module information

Outline Syllabus

. Data types
Abstract data types
Lists, stacks, queues, trees, sets, graphs

. Algorithms
Divide and conquer
Sorting and searching
Algorithms: binary search trees, minimum cost spanning trees, shortest paths, parse trees
Algorithm analysis: time and space complexity

. Basic computability, incomputable functions and the halting problem

## Learning and teaching methods

Lectures and Labs

## Bibliography*

This module does not appear to have any essential texts. To see non - essential items, please refer to the module's reading list.

## Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Portfolio of Lab Work    33.33%
Coursework   Progress Test (In person, MCQ Moodle Test, Closed Book)    33.33%
Coursework   Assignment: Programming Exercises    33.34%
Exam  Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
Exam  Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period)

### Exam format definitions

• Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
• In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
• In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
• In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Coursework Exam
30% 70%

### Reassessment

Coursework Exam
30% 70%
Module supervisor and teaching staff
Dr David Richerby, email: david.richerby@essex.ac.uk.
Dr David Richerby
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

Availability
No
No
No

## External examiner

Prof Pietro Oliveto
Southern University of Science and Technology (SUSTech)
Professor
Resources
Available via Moodle
No lecture recording information available for this module.

Further information

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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