Module Code: H6DSA
Long Title Data Structures and Algorithms
Title Data Structures and Algorithms
Module Level: LEVEL 6
EQF Level: 5
EHEA Level: Short Cycle
Credits: 10
Module Coordinator:  
Module Author: Alex Courtney
Departments: School of Computing
Specifications of the qualifications and experience required of staff


This module requires a lecturer holding a BSc degree or higher, in computing/computer science or cognate discipline.

Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Explain the theory, concepts, principles and methods of the basic and complex data structures, and various algorithms used in computer science
LO2 Use object-oriented techniques such as interfaces, inheritance, and generics to package abstract data types appropriately.
LO3 Use iterative and recursive techniques to design and implement sorting and searching algorithms
LO4 Demonstrate the use of good principles of algorithm design
LO5 Identify and apply data structures and algorithms to solve real-life problems making use of emerging technologies and programming languages
LO6 Conduct in depth algorithm analysis in terms of performance and time complexity and present the results
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

Learners should have attained the knowledge, skills and competence gained from stage 1 of the BSc (Hons) in Computing.

 

Module Content & Assessment

Indicative Content
Linear Data Structures
ArrayLists, Single and Double Linked Lists, Stack, Queue and Priority Queue, Operations on linear structures, Implementing linear structures, Exemplification of linear data structures in real world scenarios
Non-Linear Structures - Trees
General tree: Features and characteristics, . Binary trees: Exemplification of (Binary) Tree in real world scenarios, Tree organization and traversal, Tree search, Balancing a tree. Search Trees: Purpose and features of the search tree, Binary Search Tree, Building and Implementing a Binary Search Tree, Exemplification of Binary Search Tree in real world scenarios
Non-Linear Structures - Graphs
Graph’s characteristics and representation, Types of Graph: simple, directed, weighted, mixed, etc., Operations performed on graphs, Implementation of graphs using linear data structures
Recursion
Recursive approach, Fibonacci sequence, Characteristics of recursive algorithms, Exemplification of recursion for solving real-life problems, Recursive sorting
Sorting Algorithms
Algorithms: Algorithm design & development , Algorithm’s features, Experimental based algorithm’s performance estimation, Time complexity: Big O Notation . Sorting Algorithms : Bubble sort, Insertion sort , Mergesort, Quicksort.
Searching algorithms
Sequential (linear) search, Binary search.
Graph algorithms
Graph search methods, Dijkstra’s Algorithm.
Assessment Breakdown%
Coursework50.00%
End of Module Assessment50.00%

Assessments

Full Time

Coursework
Assessment Type: Formative Assessment % of total: Non-Marked
Assessment Date: n/a Outcome addressed: 2,3,4,5,6
Non-Marked: Yes
Assessment Description:
Lab exercises that involve the use of various data structures and algorithms.Feedback will be provided in oral format, or on-line through Moodle.
Assessment Type: Continuous Assessment % of total: 50
Assessment Date: n/a Outcome addressed: 2,3,4,5
Non-Marked: No
Assessment Description:
The assessment will consist of practical tasks in the form of an in-class tests that will assess learners’ knowledge and competences on data structures and algorithms. Feedback will be provided in oral format, or on-line through Moodle.
End of Module Assessment
Assessment Type: Terminal Exam % of total: 50
Assessment Date: End-of-Semester Outcome addressed: 1,6
Non-Marked: No
Assessment Description:
Terminal assessment exam taken over 2 hours consists of one mandatory question and two questions of which the student must answer one that assess students' understanding of the underlying theories and concepts.
No Workplace Assessment
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 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. The repeat exam will assess 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 Every Week 24.00
Tutorial Other hours (Practical/Tutorial) 48 Every Week 48.00
Independent Learning Independent learning (hours) 178 Every Week 178.00
Total Weekly Contact Hours 72.00
 

Module Resources

Recommended Book Resources
  • Daniel Liang, Y.. (2017), , Introduction to Java Programming and Data Structures, Comprehensive Version, Global Edition, Pearson Education Limited.
  • Goodrich, M.T. and Tamassia, R ,. (2014), ,Data Structures and Algorithms in Java ,6th ,John Willey A Sons.
This module does not have any article/paper resources
This module does not have any other resources
Discussion Note: