Data Structures and Algorithms
Computer Science and Electronic Engineering (School of)
Undergraduate: Level 5
Monday 13 January 2020
Friday 20 March 2020
25 April 2019
Requisites for this module
BSC G610 Computer Games,
BSC G612 Computer Games (Including Year Abroad),
BSC I610 Computer Games (Including Placement Year),
BSC G400 Computer Science,
BSC G401 Computer Science (Including Year Abroad),
BSC G403 Computer Science (Including Foundation Year),
BSC I101 Computer Science (Including Placement Year),
MSCIG402 Computer Science,
MSCII100 Computer Science (Integrated Masters, Including Placement Year),
BSC G1G4 Mathematics with Computing (Including Year Abroad),
BSC G1G8 Mathematics with Computing (Including Foundation Year),
BSC G1GK Mathematics with Computing,
BSC G1IK Mathematics with Computing (Including Placement Year),
BSC I1G3 Data Science and Analytics,
BSC I1G3CE Data Science and Analytics,
BSC I1GB Data Science and Analytics (Including Placement Year),
BSC I1GBCE Data Science and Analytics (Including Placement Year),
BSC I1GC Data Science and Analytics (Including Year Abroad),
BSC I1GF Data Science and Analytics (Including Foundation Year),
BENGH615 Robotic Engineering,
BENGH616 Robotic Engineering (Including Year Abroad),
BENGH617 Robotic Engineering (Including Placement Year),
BSC G111 Computing,
BSC G112 Computing (Including Year Abroad),
BSC G113 Computing (Including Placement Year),
BSC LG01 Economics with Computing,
BSC LG02 Economics with Computing (Including Year Abroad),
BSC LG03 Economics with Computing (Including Placement Year)
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.
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.
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.
. Data types
Abstract data types
Lists, stacks, queues, trees, sets, graphs
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
This module does not appear to have a published bibliography for this year.
|Assessment items, weightings and deadlines
|Coursework / exam
||Assignment 1 Programming Exercises
||Assignment 2 Programming
||120 minutes during Summer (Main Period) (Main)
Module supervisor and teaching staff
Dr Sebastian Halder
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770
No external examiner information available for this module.
Available via Moodle
Of 96 hours, 92 (95.8%) hours available to students:
4 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.
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