Module Specification

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.
1. Module Title Data Structures and Algorithms
2. Module Code COMP108
3. Year Session 2023-24
4. Originating Department Computer Science
5. Faculty Fac of Science & Engineering
6. Semester Second Semester
7. CATS Level Level 4 FHEQ
8. CATS Value 15
9. Member of staff with responsibility for the module
Professor PW Wong Computer Science P.Wong@liverpool.ac.uk
10. Module Moderator
11. Other Contributing Departments  
12. Other Staff Teaching on this Module
Mrs J Birtall School of Electrical Engineering, Electronics and Computer Science Judith.Birtall@liverpool.ac.uk
13. Board of Studies
14. Mode of Delivery
15. Location Main Liverpool City Campus
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
16. Study Hours 36

    11

    47
17.

Private Study

103
18.

TOTAL HOURS

150
 
    Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other
19. Timetable (if known)            
 
20. Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 
21. Modules for which this module is a pre-requisite:

 
22. Co-requisite modules:

 
23. Linked Modules:

 
24. Programme(s) (including Year of Study) to which this module is available on a mandatory basis:

25. Programme(s) (including Year of Study) to which this module is available on a required basis:

26. Programme(s) (including Year of Study) to which this module is available on an optional basis:

27. 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.

 
28. 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

 
29. Teaching and Learning Strategies
 

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Yes

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

Standard on-campus delivery
Teaching Method 1 - Lecture
Description: Mix of on-campus/on-line synchronous/asynchronous sessions
Teaching Method 2 - Laboratory Work
Description: On-campus synchronous sessions

 
30. 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

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

Assessment

32. EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (108) Written Exam There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :2 120 60
33. CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
  (108.3) Assignment 3 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2 0 10
  (108.1) Class Test 1 There is a resit opportunity. This is an anonymous assessment. Assessment Schedule (When) :2 0 15
  (108.2) Assignment 2 There is a resit opportunity. Standard UoL penalty applies for late submission. This is not an anonymous assessment. Assessment Schedule (When) :2 0 15