COMP SCI 7202BNA - Foundations of Computer Science B

Ngee Ann Academy - Trimester 2 - 2014

Introduces the fundamental concepts of object oriented programming. Topics include: Fundamental constructs - data types, arrays, strings and string processing, files, variables, expressions, conditionals, iteration, simple I/O. Object oriented fundamentals - methods, classes, interfaces, inheritance Algorithms and problem solving - problem solving process and strategies, simple searching and Sorting algorithms (linear and binary search, selection and insertion sort) Software development tools and techniques - testing: black box, requirements, unit Machine level representation - bits, bytes, words, number bases, representation of data, memory management.

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Course Details

Course Code	COMP SCI 7202BNA
Course	Foundations of Computer Science B
Coordinating Unit	Computer Science
Term	Trimester 2
Level	Postgraduate Coursework
Location/s	Ngee Ann Academy
Units	3
Contact	Up to 12 hours per week
Incompatible	COMP SCI 7080
Restrictions	For approved Master of Computing and Innovation, Graduate Diploma in Computer Science and Graduate Certificate in Computer Science students only.
Assessment	Written exam and/or assignments

Course Staff

Course Coordinator: Dr Alfred Fred Brown

Teaching Period	Course Coordinator
Trimester 2	Dr Cheryl Pope
Trimester 3	Dr Fred Brown

Lecturer: Mr Kwang Hua Lim

Course Timetable

The full timetable of all activities for this course can be accessed from .

The full timetable of all activities for this course can be accessed from

Course Learning Outcomes

The key learning objectives for this course are:

Design, implement and test algorithms using fundamental programming constructs and data 最新糖心Vlog.
Translate between machine level representations and demonstrate how data is represented in computers.
Identify, evaluate and use information sources to support the practice of programming, including APIs, tutorials and documentation.
Determine and compare the runtime complexity of common searching and sorting techniques and their implementations – both iterative and recursive.
Identify and apply searching and sorting techniques (linear and binary search, selection, insertion, merge, quick, bucket sorts).
Identify and apply basic data 最新糖心Vlog: linked list, stack, queue, qraph, tree (ordered, binary, balanced).
Design, implement and test solutions to problems selecting appropriate data 最新糖心Vlog and basic algorithmic techiques (brute force, divide and conquer, transform and conquer, greedy).

最新糖心Vlog Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

最新糖心Vlog Graduate Attribute	Course Learning Outcome(s)
Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised.	1,2,3,4,5,6,7
The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner.	3
An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems.	1,6,7
Skills of a high order in interpersonal understanding, teamwork and communication.	1,3
A proficiency in the appropriate use of contemporary technologies.	1,2,3,4,5,6,7
A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life.	3
An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities.	3

Learning Resources

Required Resources

There is no required text. The course will make use of various freely available resources.

Recommended Resources

If you prefer to have a textbook for reference, we recommend Walter Savitch, "Problem Solving with C++ 8th ed", Addison-Wesley, 2012, ISBN-10:0132162733, ISBN-13:9780132162739

Online Learning

The School of Computer Science uses a variety of e-learning tools to support traditional face-to-face lectures, tutorials and workshops. These tools provide access to various features including announcements, course materials, discussion boards and assessments for each course of study. Online learning resources can be accessed by selecting your course from .
Learning & Teaching Activities
Learning & Teaching Modes

This course is offered in blended learning mode with the face-to-face component offered as intensives.

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

As a guide, a 3 unit course comprises a total of 144 hours work (this includes face-to-face contact, any online components, and self directed study).

Learning Activities Summary
1. Class hierarchies, inheritance, multiple inheritance, polymorphism, namespaces.
2. Recursion, evaluating algorithms memory and runtime, algorithmic approaches to searching (linear and binary), sorting.
3. Programming data 最新糖心Vlog: stacks, queues, linked lists.
4. Trees, algorithmic strategies, review.
Specific Course Requirements

Students are expected to complete work and practice programming outside of intensive times. The lab at NAAEC has all the required resources for the course.

The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

Assessment Summary

An overview of the course assessment appears in the following Table. Details appear in the following section:

During practical lab sessions, you are encouraged to collaborate with your classmates. This extends to discussing ideas, alternatives, possible solutions and questions about material discussed in class. It does not permit copying of code from classmates. All code you submit must be your own. Practical exams are individual and you must not consult classmates in developing your solutions. 锟�

Assessment No. Form of Assessment/ Collaborative Task Indiv or Collab 锟� 锟� Weighting 锟� Learning objective covered (see 2.1 for detail)

1 Practicals Collaborative 20% 1,2,3,4,5 锟�

2 Prac Exams Individual 锟� 锟� 20% 锟� 1,2,3,4 锟�

3 Final Theory Exam Individual 锟� 锟� 30% 锟� 1,2,3 锟�

4 Final Practical Exam Individual 锟� 锟� 30% 锟� 4 锟�

Total 锟� 锟� 100%

Assessment Related Requirements

Students must achieve a minimum of 40% of available marks in the four assessment components given above and must achieve a total mark of at least 50% to be eligible to pass the course.

Students must complete all course assessment requirements and must attend lectures to be eligible to pass the course.

Course results are subject to moderation by the School of Computer Science Assessment coordinator.

Assessment Detail

Assessment 1: Practicals
Weighting: 20%
Due Dates: please note schedule on course website. Some practicals will be undertaken during class time and some must be completed in between intensive sessions.
Submission Details: Online through course website

Task: Design, test and implement solutions to the practical problems.

Scope: Each practical will assess your understanding of the course material covered during the prior session. Practical work is both summative (assessing your understanding) and formative (used to give you feedback and help you prepare for practical exams) - see schedule above. Students are encouraged to work collaboratively on practicals. Final submission must be the student’s own work, unless specified otherwise by the lecturer. ie students are encouraged to share ideas, but should not share actual code.

Criteria by which your assignment will be marked: Practicals will be assessed on design, functionality, testing and program style.

Learning objectives with this assessment (refer to section 2.1): 1,2,3,4,5

Assessment 2: Practical Exams
Weighting: 20%
Due Dates: please note schedule on course website. Practical exams will be held during intensives. Submission Details: Online through course website

Task: Design, test and implement solutions to the practical problems.

Scope: Practical exams are summative assessment and cover all topics up to the time of the practical exam - see schedule.

Criteria by which your assignment will be marked: Practical exams will be assessed on design, functionality, testing and program style.

Learning objectives with this assessment (refer to section 2.1): 1,2,3,

Assessment 3: Final Theory Exam
Weighting: 30%
Due Dates: The final theory exam will be scheduled during the examination period
Submission Details: Written Exam

Task: The theory exam assesses students depth of knowledge of programming constructs in general, tradeoffs of memory and cpu use in algorithms and data representation.

Scope: 60 minute written exam. Covers material from all of course.

Criteria by which your assignment will be marked: Correctness of answers.

Learning objectives with this assessment (refer to section 2.1): 1,2,3 Page 8 of 11

Assessment 4: Final Practical Exam
Weighting: 30%
Due Dates: The final practical exam will be held during the final intensive
Submission Details: Lab Exam

Task: Design, test and implement solutions to the practical problems.

Scope: 60 minute lab exam. Covers material from all of course.

Criteria by which your assignment will be marked: Practicals will be assessed on design, functionality, testing and program style.

Learning objectives with this assessment (refer to section 2.1): 4

Submission

All practical based assignments must be submitted via the web submission system. Please see the course website for links.

There are a few points to note about the submission of assignments:

· Assignment Submission: Assignments should not be emailed to the instructor but should be lodged via the web submission system. Note that assignments may be processed via online plagiarism prevention tools.

· Backup Copy of Assignments: All practical work is to be stored in your SVN repository. Failure to use the repository and any subsequent loss of work will not be grounds for extensions.

· Extensions of Time: Any request for an extension of time for the submission of an assignment should be made well before the due date of the assignment to the Course Coordinator. Normally, extensions will only be granted for a maximum of two weeks from the original assignment submission date. Extensions will only be granted in cases of genuine extenuating circumstances and proof, such as a doctor’s certificate, is required. Requests for extensions must be sent to the Course Coordinator using the form /student/exams/mod_arrange.html Note that supporting documentation MUST be submitted with the form.

· Failure to submit: Failure to submit an assignment on time or by the agreed extension deadline will result in penalties and may incur a fail grade. Note that a late penalty of 25% of the total available marks for that assessment item will be incurred each day an assignment is handed in late. Assignments handed in after 4 days from the due submission date will receive a mark of 0% even if a 100% mark is granted for the work. 锟硷考锟硷考锟�

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through .

Student Feedback

The 最新糖心Vlog places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the 最新糖心Vlog to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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