|Course Title||Data Structures and Algorithms|
Monday 13:00-15:00 --> Livestream lecture
Wednesday 15:00-17:00 --> Livestream lecture
Tuesday after 15:00 (week 2-10)
Friday after 17:00 (week 2-10)
Virtual Meeting: Tuesday 12:00 (week 2-10)
|Units of Credit||6|
Data structures are about how data is stored inside a computer for effective and efficient use. An algorithm is a step-by-step process for solving a problem within a finite amount of space and time. Data structures and algorithms are not only important in software design, but also in hardware design. Being proficient in data structures and algorithms are essential for good software developers, hardware developers, and system architects.
The actual content is taken from a list of subjects that constitute the basis of the tool box of every serious practitioner of computing: data types and data structures, abstract data types, dynamic data structures, analysis of algorithms and a variety of fundamental algorithms for graphs, trees and text processing.
Before commencing this course, students should
These are assumed to have been acquired in the course COMP9021.
After successfully completing this course, students will know fundamental data structures and algorithms, and they will be able to reason about their applicability, effectiveness and efficiency.
This course contributes to the development of the following graduate capabilities:
|Graduate Capability||Acquired in|
|scholarship: understanding of their discipline in its interdisciplinary context||lectures|
|scholarship: capable of independent and collaborative enquiry||problem sets, assignments, in-class (live or recorded) quizzes|
|scholarship: rigorous in their analysis, critique, and reflection||in-class (live or recorded) exercises, problem sets, assignments|
|scholarship: able to apply their knowledge and skills to solving problems||problem sets and assignments|
|scholarship: capable of effective communication||forum|
|scholarship: information literate||lectures, problem sets, assignments|
|scholarship: digitally literate||lectures, problem sets, assignments|
|professionalism: capable of independent, self-directed practice||problem sets and assignments|
|professionalism: capable of operating within an agreed Code of Practice||all course-work, by doing it yourself|
|global citizens: culturally aware and capable of respecting diversity and acting in socially just/responsible ways||interaction with your fellow students|
Lectures will include exercises where we examine the practice of formulating and proving understanding and applying specific data structures and algorithms. Problem sets aim to deepen analysis and understanding via additional examples, problems and programming exercises. The large assignment give you the chance to practice what you have learnt on a larger problem.
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 , 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:
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
The pages below describe the policies and procedures in more detail:
You should also read the following page which describes your rights and responsibilities in the CSE context:
|Assignment 1 (Weekly assessments; weeks 3-10)||8 × 2 = 16|
|Assignment 2 (MidTerm Test; week 7)||12|
|Assignment 3 (Large Assignment; week 4-10)||12|
|Final Exam (exam period)||60|
Your final overall mark will be the sum of your marks for each component provided that you pass the final exam.
To pass the course, the sum of your marks must be 50 or higher and the mark for the final exam must be 25 or higher.
|Elementary data structures and algorithms in C||week 1|
|Analysis of algorithms||week 2|
|Dynamic data structures||week 3|
|Graph data structures and algorithms||week 4-5|
|Search tree data structures and algorithms||week 7-8|
|String algorithms, Approximation||week 9|
|Randomised algorithms, Course review||week 10|
The recommended textbooks associated with this course are
The following introduction to the C programming language is recommended as a supplementary textbook:
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 the previous offering indicated that students were very satisfied with the course, but suggested to incorporate a small weekly assessment component. We will do this in this offering.
Resource created Tuesday 01 September 2020, 03:04:04 PM, last modified Saturday 03 October 2020, 01:18:03 AM.