| Module Code: |
H8ADVPROG |
|
Long Title
|
Algorithms and Advanced Programming
|
|
Title
|
Algorithms and Advanced Programming
|
| Module Level: |
LEVEL 8 |
| EQF Level: |
6 |
| EHEA Level: |
First Cycle |
| Module Coordinator: |
Adriana Chis |
| Module Author: |
Adriana Chis |
| Departments: |
School of Computing
|
| Specifications of the qualifications and experience required of staff |
MSc and/or PhD degree in computer science or cognate discipline. May also have industry experience.
|
| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Use iterative and recursive techniques to design and implement sorting and searching algorithms. |
| LO2 |
Conduct in depth algorithm analysis in terms of time complexity and present the results of analysis. |
| LO3 |
Evaluate algorithms, identify an algorithm from a range of possible options, and implement the algorithm to solve computational problems in particular contexts. |
| LO4 |
Identify and apply best practices including exception handling and design patterns in the implementation of software solutions to solve real-world 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
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| No Co-requisite modules listed |
Module Content & Assessment
| Indicative Content |
|
Algorithms
• Algorithm design and development
• Properties of algorithms (e.g. correctness, generality)
• Empirical measurements of algorithm’s performance
• Time complexity, asymptotic notations (e.g. Big O Notation, Big Omega Notation)
|
|
Sorting Algorithms
• Bubble sort
• Insertion sort
• Quicksort
• Mergesort
• Perfomance comparison of sorting algorithms
|
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Searching Algorithms
• Sequential search
• Binary search (iterative and recursive implementations)
|
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Defensive programming
• Input validation and data sanitization
• Exception handling (general exception handling, declaring new exception types)
|
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Multithreaded Programming
• Concurrent execution of threads (multitasking)
• User created threads
• Thread priorities
• Thread states and lifecycle
|
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File I/O
• Low-level file I/O
• High-level file I/O
|
| Assessment Breakdown | % |
|---|
| Coursework | 50.00% |
| End of Module Assessment | 50.00% |
AssessmentsFull Time
| Coursework |
| Assessment Type: |
Continuous Assessment |
% of total: |
50 |
| Assessment Date: |
n/a |
Outcome addressed: |
1,2,3,4 |
| Non-Marked: |
No |
Assessment Description:
The continuous assessment will consist of in-class practical tests. The practical assessments aim to evaluate students’ knowledge and ability to identify, analyse, implement and use different algorithms, and best practices to solve computational problems. Students will be assessed both on their development skills and their ability to convey understanding of the programs they have developed |
|
| End of Module Assessment |
| Assessment Type: |
Terminal Exam |
% of total: |
50 |
| Assessment Date: |
End-of-Semester |
Outcome addressed: |
1,2,3,4 |
| 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
Reassessment 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 |
No Description |
24 |
Per Semester |
2.00 |
| Laboratories |
No Description |
24 |
Per Semester |
2.00 |
| Independent Learning Time |
No Description |
77 |
Once per semester |
6.42 |
| Total Weekly Contact Hours |
4.00 |
Module Resources
| Recommended Book Resources |
|---|
-
Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser. (2014), Data Structures and Algorithms in Java, 6th Edition. John Wiley & Sons, p.736, [ISBN: 1118771338].
| | Supplementary Book Resources |
|---|
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Donald Ervin Knuth. (1997), The Art of Computer Programming: Fundamental algorithms, 3rd Edition. Addison-Wesley Professional, p.650, [ISBN: 0201896834].
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Donald Ervin Knuth. (1998), The Art of Computer Programming: Sorting and searching, 2nd Edition. Addison-Wesley Professional, p.780, [ISBN: 0201896850].
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Paul Deitel,Harvey Deitel. (2017), Java How to Program, Early Objects, Pearson, 11th Edition, 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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