Module Details

Module Code: COMP C7012
Full Title Algorithms
Valid From: Semester 1 - 2019/20 ( June 2019 )
Language of Instruction:English
Duration: 1 Semester
Credits: 5
Module Author Michelle Graham
Departments: Unknown
Module Description: Students completing this module will be able to analyse, select and implement appropriate algorithms for a range of problems.
 
Module Learning Outcome
On successful completion of this module the learner will be able to:
# Module Learning Outcome Description
MLO1 Implement a selection of well-known algorithms.
MLO2 Analyse the efficiency of an algorithm.
MLO3 Choose the most appropriate algorithm (custom or existing) for use in a given scenario.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named DkIT 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
 
Indicative Content
Algorithm Design
What is an algorithm, properties of an algorithm, debugging algorithms
Array manipulation
Insertion, deletion, removal of duplicates, partitioning, merging
Algorithm analysis
Big O notation, comparison of algorithms.
Searching algorithms
Design and implementation of a selection of searching algorithms (linear search & binary search)
Sorting algorithms
Design and implementation of a selection of sorting algorithms (selection sort and bubble sort)
Recursion
Recursive design and implementation, when to use recursion, implementing recursive-based algorithms (merge sort, quick sort, revisiting binary search)
Module Content & Assessment
Assessment Breakdown%
Course Work60.00%
End of Module Formal Examination40.00%
Special Regulation
 

Assessments

Full Time

Course Work
Assessment Type Class Test % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Week 6 Learning Outcome 1
Duration in minutes 120
Assessment Description
Lab exam
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Every Week Learning Outcome 1,3
Duration in minutes 0
Assessment Description
Formative assessment comprised of weekly exercise sets.
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Week 12 Learning Outcome 1,2,3
Duration in minutes 0
Assessment Description
Final project in which students are provided with a problem and required to select and implement appropriate algorithms (justifying the selection through analysis of candidate algorithms) to solve this problem.
No Project
No Practical
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 40
Marks Out Of 0 Pass Mark 0
Timing End-of-Semester Learning Outcome 1,2
Duration in minutes 120
Assessment Description
End of semester written examination.

Part Time

Course Work
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Every Week Learning Outcome 1,3
Duration in minutes 0
Assessment Description
Formative assessment comprised of weekly exercise sets.
Assessment Type Class Test % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Week 6 Learning Outcome 1
Duration in minutes 120
Assessment Description
Lab exam
Assessment Type Continuous Assessment % of Total Mark 20
Marks Out Of 0 Pass Mark 0
Timing Week 12 Learning Outcome 1,2,3
Duration in minutes 0
Assessment Description
Final project in which students are provided with a problem and required to select and implement appropriate algorithms (justifying the selection through analysis of candidate algorithms) to solve this problem.
No Project
No Practical
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 40
Marks Out Of 0 Pass Mark 0
Timing End-of-Semester Learning Outcome 1,2
Duration in minutes 120
Assessment Description
End of semester written examination.
Reassessment Requirement
A 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.

DKIT reserves the right to alter the nature and timings of assessment

 

Module Workload & Resources

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Practical Contact 2 * 2 hour labs covering a combination of practical (development and design) and theoretical (concepts and theory of algorithms) content Every Week 4.00 4
Directed Reading Non Contact Course-related materials for discussion in class Every Week 1.00 1
Independent Study Non Contact Practice and extra study to reinforce classwork Every Week 3.00 3
Total Weekly Learner Workload 8.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Practical Contact 2 * 2 hour labs covering a combination of practical (development and design) and theoretical (concepts and theory of algorithms) content Every Week 4.00 4
Directed Reading Non Contact Course-related materials for discussion in class Every Week 1.00 1
Directed Reading Non Contact Practice and extra study to reinforce classwork Every Week 3.00 3
Total Weekly Learner Workload 8.00
Total Weekly Contact Hours 4.00
 
Resources
Recommended Book Resources
  • Robert Sedgewick & Kevin Wayne. (2015), Algorithms, 4th. Addison-Wesley Professional, p.984, [ISBN: 978-013438468].
Supplementary Book Resources
  • Robert Sedgewick & Kevin Wayne. (2016), Computer Science: An Interdisciplinary Approach, 1st. Addison-Wesley Professional, p.1168, [ISBN: 978-013407642].
  • George T. Heineman, Gary Pollice & Stanley Selkow. (2015), Algorithms in a Nutshell: A Practical Guide, 2nd. O'Reilly Media, p.425, [ISBN: 978-149194892].
  • Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein. (2009), Introduction to Algorithms, 3rd. MIT Press, p.1312, [ISBN: 978-026203384].
This module does not have any article/paper resources
This module does not have any other resources
 
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