COURSE SPECIFICATION
Course code
Course title
Department
Level (UG)
CSC 310
Algorithms and Complexity Analysis
Mathematics/Computer Science/Statistics &
Informatics
2
Level 3
Course Coordinator
Dr. M. O. Eze
Credit unit
Official phone number and email Mobile: 08028669172
address
E-Mail: eze_monday@yahoo.com
Office Hours
NIL
Other staff (if applicable)
Official phone number and email Dr. M.O. Eze (eze_monday@yahoo.com)
address
Monday –Friday (8.am – 4pm)
Office Hours
Time Table is Being Awaited
Lecture Time
Time Table is Being Awaited
Lecture Venue
Time Table is Being Awaited
Tutorial Time
Tutorial Venue
ICT Lab/Language Lab.
For academic year
2014/15
Contact hours for the semester
Lectures
[26 hours ]
Labs/Seminars
[10 hours]
Assessment
Method
Proportion of marks
Mid Semester Exam [15]%
Coursework
[15]%
Examination
[70]%
This course is to be taken as part of the B.Sc. Computer Science
following programmes:
__________________________________________________________________________
Directorate of Academic Planning, FUNAI
COURSE AIMS- ALIGNMENT WITH FUNAI’S VISION, MISSION AND PROGRAMME
OBJECTIVE
The aim of this course is to help the students appreciate Computational Algorithms in a more
advanced level, than they had covered in the earlier CSC (101, 201, 202, 204, 205 etc)
courses. It guides students to practical steps in algorithm development. Particularly, the
students are required to learn the formal methods related to algorithm performance. It
prepares them for other advanced programming and design courses to be studied in the final
year. It also repositions them to be able to fit into the industry, and be ready to tackle some of
the practical issues expected during their Industrial Work Experience (Year 3 Semester 2).
This course is very rich and should give the students a level of versatility in problem solving.
It also prepares them to be able to handle their final year projects by themselves.
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INTENDED LEARNING OUTCOMES
After completing this course, the student should be able to:
1.
2.
3.
4.
5.
6.
Define Algorithm
Understand why this course is very important for any Computer Scientist, no matter the
area of specialization.
Understand the concept of Algorithm Complexity and Complexity Analysis.
Understand the Time and Space Tradeoffs in Complexity Analysis, among other things.
Explore Numeric Algorithms and their applications
Build more understanding in the following areas already covered in the CSC 202/204:
-
Sequential and binary search algorithms
Sorting algorithms
Binary Search Tress
Hash tables, etc.
7.
Understand the Big O Notation, other notations, and other key issues related to
complexity and algorithm analysis.
8. Understand the factors that affect program efficiency and be able to tell which algorithm
is more efficient than others, and why it is so.
9. Understand some Specific Algorithms eg. Recursive Algorithm, Randomized
Algorithms, Parallel Algorithms, Numeric Algorithms, and others as may be introduced
by the lecturer.
10. Real Life/Practical Applications of Algorithm.
11. Other Current Issues as may be Introduced by Lecturer.
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LEARNING AND TEACHING METHODS
This course will be delivered through a combination of lectures, seminar, tutorials and labs
that will feature student-centred activities via power point presentations, whiteboard
illustrations and practical demonstration in the laboratory. The course will be delivered
through a combination of internet and intranet support activities including tutorials, group
discussion forums and individual learning.
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INDICATIVE CONTENT
Directorate of Academic Planning, Federal University Ndufu-Alike, Ikwo (FUNAI)
2
Lecture/seminar programme
FUNAI
Wk
Lecture
Session
Topic/Reading for private
study
Tasks/Think points for
private study
Lecturer
4
1
Exploring the Theory of
Algorithm Complexity and
Analysis
Dr. M.O. Eze.
5
2
Theoretical Analysis of
Algorithms.
6
3
Algorithm CASE Analysis
7
4
8
5
Complexity and Rules of
Thumbs for Complexity
Determination.
Sample Computations/
Practical Solutions
9
6
10
7
A robust introduction of the
subject area will be tackled
here. Key notations,
theories, illustrations and
motivations for studying this
course will be vigorously
pursued.
The theoretical concepts will
be presented at this point.
Some of the concepts such
as Big O notation,
Big-Omega notation
Big-Theta notation,
Hidden constant,
Logarithmic time, etc will be
discussed.
The Best, Worst and
Average CASE analysis will
be presented, PLUS other
related issues.
At least three rules of thumb
will be studied and
discussed.
A number of practical
questions are to be explored
and solved. This will
involved both class room
solutions, take home and
group solutions.
Key proofs will be pursued
at this stage of this course.
Mid–Semester Examination
11
8
Advancements in
Algorithm Studies I
12
9
Advancements in
Algorithm Studies II
13
10
Practical Session: Case
Study I
14
11
Advancements in
Algorithm Studies III
Proof of Algorithm
Correctness
Mid–Semester Exam
Issues related to
performance will be further
pursued, among other things.
Issues related to
visualization of algorithm
complexity analysis graphs
will be studies, plus other
related issues.
Students + Lecturers
Brainstorming on Real life
Applications of
Algorithms/Complexity,
Industrial related issues, etc.
Reviews and Reflections on
issues already covered will
be done, among other things.
Further advancements in
Algorithm/Complexity
Studies will be pursued.
Example Recursive
Algorithms, etc.
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze. &
Other Invigilators
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze.
Directorate of Academic Planning, Federal University Ndufu-Alike, Ikwo (FUNAI)
3
15
12
Advancements in
Algorithm Studies IV
16
13
Advancements in
Algorithm Studies V
17
14
Advancements in
Algorithm Studies VI
18
15
19
16
20-21
22
17
18
Practical Session: Case
Study 3
Practical Session: Case
Study 4
Revision
Exams
Further advancements in
Algorithm/Complexity
Studies will be pursued.
Example Parallel Algorithms
and other related areas.
Further advancements in
Algorithm /Complexity
Studies will be pursued.
Example Automata Theory
and Computability, etc.
Discussion will focus on
Current Issues as well as
Applications.
Real Life Projects
Dr. M.O. Eze.
Real Life Projects
Dr. M.O. Eze
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze.
Dr. M.O. Eze.
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INDICATIVE KEY LEARNING RESOURCES
Reading list
This core text for this study is listed as follows. The lecturer will provide a comprehensive
note/power point slide for the benefit of the students. Other suggested supplementary reading
materials are also listed below.
Core textbook
0.
G.T. Heinneman, G. Pollice & S. Selkow, "Algorithms in a Nutshell: a Desktop Quick Reference"
O’Reilly Media, Inc., Sebastopol USA, 2009
Supplementary reading
1.
T. Cormen, C. Leiserson,R. Rivest & C. Stein, "Introduction to Algorithm", 3rd Ed, The MIT
Press, Massachusetts, 2009
2.
B.L. Jones & P. Aitken, P., Teach Yourself C in 21 Days, 6th Edition, Sams Publishing, 2003
CONTINIOUS ASSESSMENT
The Intended Learning Outcomes are assessed through:
Assessment
Mid semester Exams
Coursework (Assignment)
Semester Exams
Weight
15%
15%
70%
Deliverables - important dates
Directorate of Academic Planning, Federal University Ndufu-Alike, Ikwo (FUNAI)
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Ensure that you make a careful note of when the assessment tasks are due in for this course. Try not to
leave working on these tasks until the last minute – this is stressful for you and tends to lead to poor
quality work. Remember that you have several assessments (for different courses) due the same week
and you will need to plan for this.
Assessment
Mid semester exam-
Due date
FUNAI WEEK 10
To be held at the regular
class time and venue
Coursework
Semester Exam
TO BE DETERMINED BY
COURSE
COORDINATOR
FUNAI WEEK 22-23
Feedback & Result
14 working days after the
assessment
14 working days after the
assessment
Feedback on your work
The university is committed to providing you with written feedback for all assessed coursework within
14 working days from the submission date. You will get feedback on your performance on a feedback
form which will be returned to you. If you do not receive feedback within this time, then you should
first contact the course leader. If it proves necessary, you should then contact the Head of Department.
Submitted coursework, including your final year project, will not be returned to you. This is true for
all coursework, in all courses and at all levels, and does not apply to only this course. We must keep
the original copy of all coursework to provide the external examiners with a complete record of your
work.
Late coursework
It is the University policy to accept and grade all late items of coursework (up to the published latest
date for submission). There is no such thing as 'an extension'. You cannot negotiate new deadlines,
and you do not need to get agreement about handing in your work late from the course leader or any
other member of staff. Late coursework submissions are, however, subject to penalties (capping) that
determine the maximum grade that you can achieve depending upon how late the work is. The current
penalty scale can be found below:
The following caps to be uniformly applied, in the absence of relevant mitigating circumstances
accepted by the BoE:
Up to 1 working day late
Up to 2 working days late
Up to 5 working days late
Up to 10 working days late
Up to 15 working days late
More than 15 working days late
Mark capped at 90%
Mark capped at 80%;
Mark capped at 70%;
Mark capped at 60%;
Mark capped at 50%;
Mark capped at 0%.
A working day is here defined as Monday to Friday at any time of year, with the exception of Nigeria
national holidays. Students with mitigating circumstances can apply to have penalties removed via
submission of the appropriate form and evidence within 7 days of the submission deadline. How to do
this can be found in the University Assessment Policy and Procedure.
Directorate of Academic Planning, Federal University Ndufu-Alike, Ikwo (FUNAI)
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Planning your time
i.
Students are expected to attend all classes including seminars and laboratory
sessions for each course. It is mandatory for students to have a minimum attendance of
75% in this course to be eligible to take the final semester examination.
ii.
Note: Instructors are not required to provide mid semester test make-up.
Directorate of Academic Planning, Federal University Ndufu-Alike, Ikwo (FUNAI)
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