Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title DATA STRUCTURES AND ALGORITHMS
Code COMP108
Coordinator Prof PW Wong
Computer Science
P.Wong@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2019-20 Level 4 FHEQ Second Semester 15

Aims

To introduce the notation, terminology, and techniques underpinning the study of algorithms.
To introduce basic data structures and associated algorithms.
To introduce standard algorithmic design paradigms and efficient use of data structures employed in the development of efficient algorithmic solutions.


Learning Outcomes

(LO1) Be able to describe the principles of and apply a variety of data structures and their associated algorithms;

(LO2) Be able to describe standard algorithms, apply a given pseudo code algorithm in order to solve a given problem, and carry out simple asymptotic analyses of algorithms;

(LO3) Be able to describe and apply different algorithm design principles and distinguish the differences between these principles;

(LO4) Be able to choose and justify the use of appropriate data structures to enable efficient implementation of algorithms;

(S1) Numeracy/computational skills - Reason with numbers/mathematical concepts

(S2) Numeracy/computational skills - Problem-solving

(S3) Critical thinking and problem-solving - Critical analysis


Syllabus

 

Basics of algorithms (6 lectures)
What is an algorithm, design of pseudo code algorithm, basic notion of asymptotics and worst case analysis of running time.

Basic data structures and associated algorithms (12 lectures)
Arrays and linked lists
Stacks and queues
Trees and graphs
Hash table

Algorithmic design techniques and efficient use of data structures (18 lectures)
Basic top down approach – searching and sorting
Divide-and-conquer approach – searching and sorting
Greedy approach – graph algorithms
Dynamic programming approach


Teaching and Learning Strategies

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Yes

Teaching Method 2 - Laboratory Work
Description:
Attendance Recorded: Yes


Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 36

    11

    47
Timetable (if known)              
Private Study 103
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Written Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :2  120 minutes.    60       
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Assignment 1 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2  20 hours expected    20       
Assignment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2  20 hours expected    20       

Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.