Course Outline

Contents

• Course Details
• Course Summary
• Assumed Knowledge
• Student Learning Outcomes
• Teaching Strategies
• Teaching Rationale
• Student Conduct
• Assessment
• Course Schedule
• Resources for Students
• Course Evaluation and Development

Course Details

Course Code	COMP9020
Course Title	Foundations of Computer Science
Convenor	Michael Thielscher
Admin	Michael Schofield
Classes	Day Start Time End Time Room Who Wednesday 11:00 13:00 Ainsworth G03 (Building K-J17) Michael Thielscher Friday 15:00 17:00 Ainsworth G03 (Building K-J17) Michael Thielscher
Consultations	Day Start Time End Time Room Who Wednesday (from week 2) 13:00 14:00 Ainsworth 101 (K-J17) + Online Kamiyu Hijikata Friday 12:00 13:00 Online Michael Thielscher
Units of Credit	6
Course Website	http://www.cse.unsw.edu.au/~cs9020
Handbook Entry	http://www.handbook.unsw.edu.au/postgraduate/courses/current/COMP9020.html

Course Summary

The scope is: mathematical methods for designing correct and efficient programs; mathematics for algorithm analysis; logic for proving and verification.

The actual content is taken from a list of subjects that constitute the basis of the tool box of every serious practitioner of computing: set, function and relation theory; propositional logic and boolean algebras; graph theory and trees for algorithmic applications; induction, recursion and recurrence relations; order of growth of functions; structured counting (combinatorics); discrete probability.

Assumed Knowledge

None

Student Learning Outcomes

After successfully completing this course, students will have developed an increased level of mathematical maturity to assist with the fundamental problem of

1. finding and formulating properties of programs, especially their correctness w.r.t. given requirements and specifications
2. analysing and proving properties of programs, in particular their correctness and runtime behaviour

Online quizzes, mid-term assignment and final exam will ensure that students have acquired this level of mathematical maturity.

This course contributes to the development of the following graduate capabilities:

Graduate Capability	Acquired in
Scholars capable of independent and collaborative enquiry, rigorous in their analysis, critique and reflection, and able to innovate by applying their knowledge and skills to the solution of novel as well as routine problems	lectures, in-class exercises, problem sets, quizzes
Professionals capable of ethical, self-directed practice and independent lifelong learning	problem sets, quizzes
Global citizens who are culturally adept and capable of respecting diversity and acting in a socially just and responsible way	interaction with your lecturer and fellow students

Teaching Strategies

• Lectures introduce concepts and show examples
• Problem sets reinforce concepts, provide additional examples and allow students to solve problems
• Quizzes allow students to demonstrate their problem-solving skills

Teaching Rationale

Lectures will include exercises where we examine the practice of formulating and proving mathematical properties of relevance to Computer Science. Problem sets and quizzes aim to deepen analysis and understanding via additional examples and problems.

Student Conduct

The Student Code of Conduct ( Information , Policy ) sets out what the University expects from students as members of the UNSW community. As well as the learning, teaching and research environment, the University aims to provide an environment that enables students to achieve their full potential and to provide an experience consistent with the University's values and guiding principles. A condition of enrolment is that students inform themselves of the University's rules and policies affecting them, and conduct themselves accordingly.

In particular, students have the responsibility to observe standards of equity and respect in dealing with every member of the University community. This applies to all activities on UNSW premises and all external activities related to study and research. This includes behaviour in person as well as behaviour on social media, for example Facebook groups set up for the purpose of discussing UNSW courses or course work. Behaviour that is considered in breach of the Student Code Policy as discriminatory, sexually inappropriate, bullying, harassing, invading another one's privacy or causing any person to fear for their personal safety is serious misconduct and can lead to severe penalties, including suspension or exclusion from UNSW.

If you have any concerns, you may raise them with your lecturer, or approach the School Ethics Officer , a Grievance Officer , or one of the

Student Representatives

Plagiarism is defined as using the words or ideas of others and presenting them as your own. UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:

• Plagiarism and Academic Integrity
• UNSW Plagiarism Management Procedure

Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism. In particular, you are also responsible that your assignment files are not accessible by anyone but you by setting the correct permissions in your CSE directory and code repository, if using. Note also that plagiarism includes paying or asking another person to do a piece of work for you and then submitting it as your own work.

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW staff and students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

If you haven't done so yet, please take the time to read the full text of

• UNSW's policy regarding academic honesty and plagiarism

The pages below describe the policies and procedures in more detail:

• Student Code Policy
• Student Misconduct Procedure
• Plagiarism Policy Statement
• Plagiarism Management Procedure

You should also read the following page which describes your rights and responsibilities in the CSE context:

• Student responsibilities and conduct

Assessment

Item	Topics	Due	Marks
Online Quizzes	All topics	Weeks 3-6, 8-10	14%
Online Mid-term Assignment	All topics from week 1-5	Week 6	26%
Online Final Exam	All topics from week 1-9	Exam period	60%

Each of the 7 weekly assignments is worth 2 marks (7 * 2 = 14).

Your overall score in the course will be the maximum of:

• weekly marks + mid-term + exam
• weekly marks + exam * (86/60)
• mid-term + exam * (74/60)
• exam * (100/60)

In other words: if you do better in the final exam, then the weekly quizzes and/or your mid-term assignment will be ignored.

To pass the course, your overall score must be 50 or higher and your mark for the final exam must be 25 or higher. If you meet both conditions, your overall score will be your mark for this course.

Course Schedule

Week	Lectures	Assessments
1	Numbers, Sets, Formal Languages	–
2	Logic, Proofs, Boolean Algebra	Quiz
3	Functions and Relations	Quiz
4	Equivalence and Order Relations	Quiz
5	Graphs	Quiz
6	–	Mid-term online assignment
7	Induction, Recursion, Big-Oh Notation	Quiz
8	Counting and Probability	Quiz
9	Conditional Probability	Quiz
10	Expected Values, Course Review	–

Resources for Students

The primary textbook associated with this course is

• [RW] KA Ross and CR Wright, Discrete Mathematics, 5th edition, Pearson, 2003.

This has been the recommended textbook for the course for the last 10 or more years. The following comprehensive lecture notes, which are from a similar course at MIT, provide supplementary material:

• [LLM] E Lehman, FT Leighton and A Meyer, Mathematics for Computer Science, Creative Commons 2015.

Course Evaluation and Development

This course is being continuously improved and we will conduct a survey through UNSW's myExperience process at the end of session to obtain feedback on the quality of the various course components. Your participation in the survey will be greatly appreciated. Students are also encouraged to provide informal feedback during the session, and to notify the lecturer-in-charge of any problems as soon as they arise.

Student feedback from last offerings indicated that students were very satisfied with the course and in particular the newly added "warming up" exercises at the beginning of each problem set. We will continue to use, and further improve, these exercises in this offering.