CE204-5-SP-CO:
Data Structures and Algorithms
2016/17
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Undergraduate: Level 5
Current
15
06 March 2009
Requisites for this module
(none)
(none)
(none)
(none)
(none)
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 G1GK Mathematics with Computing,
BSC G1IK Mathematics with Computing (Including Placement Year),
MODUGH46MB Modular Undergraduate: Computing and Electronic Systems (Module Based),
OCCUGH46MB Modular Undergraduate: Computing and Electronics Systems (Module Based)(Non-Assessed),
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)
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.
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. Explain the main concepts of computability and how some problems have no algorithmic solution.
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
No information available.
No information available.
STUDENTS SHOULD NOTE THAT THIS MODULE INFORMATION IS SUBJECT TO REVIEW AND CHANGE
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Assignment 1 Programming Exercises |
|
33.33% |
| Coursework |
Assignment 2 Programming |
|
33.34% |
| Written Exam |
Progress Test |
|
33.33% |
| Exam |
Main exam: 120 minutes during Summer (Main 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.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Mike Sanderson
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770
Yes
No
No
Dr Ke Chen
The University of Manchester
Senior Lecturer
Available via Moodle
Of 64 hours, 22 (34.4%) hours available to students:
42 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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