| Module Code: |
H8DS |
|
Long Title
|
Data Structures
|
|
Title
|
Data Structures
|
| Module Level: |
LEVEL 8 |
| EQF Level: |
6 |
| EHEA Level: |
First Cycle |
| Module Author: |
Isabel O'Connor |
| Departments: |
School of Computing
|
| Specifications of the qualifications and experience required of staff |
Master’s and/or PhD degree in computing or cognate discipline. May have industry experience also.
|
| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Explain the theory, concepts and principles of linear and non-linear data structures used in computer science. |
| LO2 |
Use object-oriented concepts and generics to develop abstract data types and algorithms. |
| LO3 |
Identify, evaluate and implement software solutions that use complex data structures and related algorithms to solve a number of fundamental real-world computational problems. |
| Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
|
| No recommendations listed |
Co-requisite Modules
|
| No Co-requisite modules listed |
| Entry requirements |
See section 4.2 Entry procedures and criteria for the programme including procedures recognition of prior learning
|
Module Content & Assessment
| Indicative Content |
|
Introduction
Review of Software Testing; writing a unit test; unit testing will be used throughout the module, where appropriate, when implementing data structures and their corresponding operations.. Introduction to Data Structures (e.g. linear and non-linear)
|
|
Recursion
The concept of recursion. Fibonacci sequence. Example of real-life problems using recursion
|
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Linear Data Structures
ArrayLists. Stacks. Queues. Priority Queues. Single Linked Lists. Double Linked Lists. Operations on linear structures
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|
Binary Trees
Tree Data Structure – characteristics. Tree organization. Tree traversal. Balancing a tree
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Search Trees
Tree search characteristics and applicability. Binary search trees. Balanced binary search. Implementing a binary search tree
|
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Graphs
Representation of graphs. Types of graphs (e.g. undirected, directed, and weighted graphs). Graph traversals algorithms (i.e. depth- and breadth-first traversals). Common graph algorithms – shortest-path algorithm (e.g. Dijkstra’s algorithm)
|
| Assessment Breakdown | % |
|---|
| Coursework | 50.00% |
| End of Module Assessment | 50.00% |
AssessmentsFull Time
| Coursework |
| Assessment Type: |
Formative Assessment |
% of total: |
Non-Marked |
| Assessment Date: |
n/a |
Outcome addressed: |
1,2,3 |
| Non-Marked: |
Yes |
Assessment Description:
The formative assessment will consist of ongoing independent and group programming practical tasks. In-class discussions and oral feedback will be provided throughout these activities. |
|
| Assessment Type: |
Continuous Assessment |
% of total: |
50 |
| Assessment Date: |
n/a |
Outcome addressed: |
1,2,3 |
| Non-Marked: |
No |
Assessment Description:
The continuous assessment will consist of in-class practical tests. The practical assessments aim to evaluate the students’ knowledge and ability to identify, evaluate, implement and use data structures and algorithms to solve computational problems. Students will be assessed both on their development skills and their ability to convey understanding of the data structures and algorithms they have developed. |
|
| End of Module Assessment |
| Assessment Type: |
Terminal Exam |
% of total: |
50 |
| Assessment Date: |
End-of-Semester |
Outcome addressed: |
1,2,3 |
| Non-Marked: |
No |
Assessment Description:
End-of-Semester Final Examination |
|
| Reassessment Requirement |
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
|
Reassessment Description
Repeat examinationReassessment of this module will be via repeat examination which evaluates all learning outcomes.
|
NCIRL reserves the right to alter the nature and timings of assessment
Module Workload
| Module Target Workload Hours 0 Hours |
| Workload: Full Time |
| Workload Type |
Workload Description |
Hours |
Frequency |
Average Weekly Learner Workload |
| Lecture |
Classroom & Demonstrations (hours) |
24 |
Per Semester |
2.00 |
| Tutorial |
Other hours (Practical/Tutorial) |
36 |
Per Semester |
3.00 |
| Independent Learning |
Independent learning (hours) |
190 |
Per Semester |
15.83 |
| Total Weekly Contact Hours |
5.00 |
Module Resources
| Recommended Book Resources |
|---|
-
Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser. (2014), Data Structures and Algorithms in Java, John Wiley & Sons, p.736, [ISBN: 1118771338].
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Mark Allen Weiss. (2010), Data Structures & Problem Solving Using Java, Addison-Wesley Longman, p.985, [ISBN: 0321541405].
| | Supplementary Book Resources |
|---|
-
Donald Ervin Knuth. (1997), The Art of Computer Programming: Fundamental algorithms, Addison-Wesley Professional, p.650, [ISBN: 0201896834].
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Paul Deitel,Harvey Deitel. (2017), Java How to Program, Early Objects, Pearson, p.1296, [ISBN: 9780134743356].
| | This module does not have any article/paper resources |
|---|
| This module does not have any other resources |
|---|
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