Contents

Course Details

Course Code COMP2521
Course Title Data Structures and Algorithms
Course Convenor Sim Mautner
Lecturer Sim Mautner
Admin Kevin Luxa and Ethan Brown
Course Contact Email cs2521@cse.unsw.edu.au
All admin-related queries must be sent to this email address.
Course Website https://cgi.cse.unsw.edu.au/~cs2521/23T2/
Handbook Entry https://www.handbook.unsw.edu.au/undergraduate/courses/2023/COMP2521/

Course Summary

The goal of this course is to deepen your understanding of data structures and algorithms and how these can be employed effectively in the design of software systems. It is an important course in covering a range of core data structures and algorithms that will be used in context in later courses. You explore these ideas in lectures, tutorials, lab exercises, quizzes and assignments. Assessment involves lab exercises, quizzes, assignments and a final exam involving both practice and theory. At the end of the course, we want you to be a solid programmer, with knowledge of a range of useful data structures and programming techniques, and ready to continue with further specialised studies in computing.

Topics

This course provides an introduction to the structure, analysis and usage of a range of fundamental data types and the core algorithms that operate on them. Key topics are:

  • Recursion
  • Analysis of algorithms
  • Abstract data types
  • Binary search trees
  • Balanced search trees
  • Graphs
  • Sorting algorithms
  • Heaps
  • Hashing
  • Tries

Executive Summary

A summary of the critical things to know about COMP2521:

  • attempt all of the lab exercises, quizzes and assignments yourself
  • always try to produce a better program than last time
  • in lectures, think critically about what's being said/shown
  • the textbook is a useful reference source beyond this course
  • assessment:
    • labs: 15%
    • quizzes: 10%
    • assignments: 35%
    • final exam: 40%
  • enjoy the course!

Assumed Knowledge

The official pre-requisite for this course is either COMP1511 or COMP1917 or COMP1921.

Whether or not you satisfy the pre-requisite, we assume that:

  • You can program in the C programming language, and are familiar with arrays, strings, pointers, and dynamic memory allocation
  • You are able to design, implement, debug, test and document small programs (up to several hundred lines of code) in C or a C-like language
  • You are familiar with the Linux environment on the CSE computers

Installing Linux, possibly as a virtual machine, on your own computer would be a major bonus.

Course Aims

The aim of this course is to get you to think like a computer scientist . This certainly sounds like a noble goal... but what does it really mean? How does a scientist , let alone a computer scientist, actually think?

What many types of scientists try to do is understand natural systems and processes: a geologist, for example, tries to understand the structure of the earth; a biologist tries to understand living organisms; a chemist tries to understand materials and reactions, and so on.

Computer scientists don't, as the name might suggest, simply try to understand the structure and behaviour of computers, but are more concerned with understanding software systems (and the interaction between the software and the hardware on which it runs). Also, unlike other scientists, computer scientists frequently build the objects that they study.

During this course, we'll be looking at ways of creating, analysing and understanding software. Ultimately, you should be able to answer the question, <q>is this piece of software any good?</q> and be able to provide sound reasons to justify your answer.

This course follows on from introductory C programming courses: COMP1511, COMP1917, or COMP1921. We cover additional aspects of the C programming language that were not covered in those courses, and also look at some programming tools which were not covered (in detail) earlier. However, this course is not simply a second C programming course: the focus is on the ideas and abstractions behind the data structures and algorithms that are used.

COMP2521 is a critical course in the study of computing at UNSW, since it deals with many concepts that are central to future studies in the area. Whether you are studying Computer Science, Software Engineering, Bioinformatics, Computer Engineering, or even a discipline outside the realm of computing, understanding a range of algorithms and data structures and how to use them will make you a much more effective computing problem solver in the future.

Course Learning Outcomes (CLO)

After completing this course, students will:

  1. Be familiar with fundamental data structures and algorithms
  2. Be able to analyse the performance characteristics of algorithms
  3. Be able to measure the performance behaviour of programs
  4. Be able to choose/develop an appropriate data structure for a given problem
  5. Be able to choose/develop appropriate algorithms to manipulate chosen data structures
  6. Be able to reason about the effectiveness of data structures and algorithms for solving a given problem
  7. Be able to package a set of data structures and algorithms as an abstract data type
  8. Be able to develop and maintain software systems in C that contain thousands of lines of code

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, assignments
scholarship: capable of independent and collaborative enquiry lab work, assignments
scholarship: rigorous in their analysis, critique, and reflection tutorials
scholarship: able to apply their knowledge and skills to solving problems tutorials, lab work, assignments
scholarship: ethical practitioners all course-work, by doing it yourself
scholarship: capable of effective communication tutorials
scholarship: digitally literate everywhere in CSE
leadership: enterprising, innovative and creative assignments
leadership: collaborative team workers lab work, assignments
professionalism: capable of operating within an agreed Code of Practice all prac work

Teaching Rationale

Computer science is, to a large extent, a practical discipline, and so COMP2521 has an emphasis on practice. Lectures will include exercises where we examine the practice of developing and analysing programs. The aim of tutorials is to develop analysis and understanding via practical case studies. Lab classes also provide practice in program development and analysis. Assignments provide large case studies of software development.

Teaching Strategies

COMP2521 involves lectures, tutorials, labs, quizzes and assignments.

Lectures aim to convey basic information about the course content and to model the practices and techniques involved in software development. The most important components of the course, however, are the tutorials, labs and assignments. Tutorials aim to clarify and refine the knowledge that you got from lectures, and from reading the textbook and notes. Labs and assignments are where you get to put together and practise all of the ideas from the lectures and tutorials. The only way to develop the skills to do effective software development is by practising them. If you slack off on the assignments and lab exercises (or, worse, rely on someone else to do them for you), you're wasting the course's most valuable learning opportunities.

The university requires us to assess how well you have learned the course content, and the primary approach to achieving this is via a final exam. A final exam is the ultimate summative assessment tool; it gives you a chance, at the end of the course, to demonstrate everything that you've learned. Labs and assignments are a learning tool, not an assessment tool, so in an ideal world, we would have them as pure learning exercises and award no marks for them. However, to give a more concrete incentive to do them (in a timely fashion), there are marks tied to them.

Lectures

Each week, there will be four hours of lectures during which theory and practical demonstrations will be presented. Lectures convey a small amount of information about the course content, but their main aim is to try to stimulate you to think about concepts and techniques.

Lectures will be delivered:

* Tuesday 9am-11am online on YouTube

* Friday 9am-11am in person at Clancy Auditorium

All lectures will be available via Echo360 after the lecture. We endeavour to also make lectures available over YouTube (the online lectures will definitely be available over YouTube).

Tutorial/Lab Classes

Every week starting from Week 1, you will be expected to attend a three hour tutorial/lab class to clarify ideas from lectures and work through lab exercises. Classes begin with a 1 hour tutorial, followed by a 2 hour lab.

Most tutorials will be face-to-face, but there will be some online classes. Online classes will run via a system called Zoom. Access online classes here: https://webcms3.cse.unsw.edu.au/COMP2521/23T2/reso...

Tutorials

Tutorials aim to clarify ideas from lectures and to get you to think about design/analysis issues. The aim of the class is not to simply get the tutor to give you the answers; the aim is to focus on just one or two of the exercises and work through them in detail, discussing as many aspects, alternative approaches, fine details, etc. as possible. You must be active and ask questions in tutorials.

You should make sure that you use this time effectively by examining in advance the material to be covered in each week's tutorial. This means that you are coming to class prepared to ask any questions that you may have, and generally participate in class by offering suggestions - this will ensure that you get the most possible out of the tutorial. Your tutors are there to help you clear up any misunderstandings or to understand topics in more depth. The tutorial questions will be linked to the class webpage in the week before each tutorial. There are no marks for tutorial attendance, however, it is your chance to have all your questions answered.

Labs

Labs aim to give you practice in problem solving and program development. Each week, there will be a few exercises to work on. These exercises will be released in the week preceding the lab class. Labs are to be completed individually.

Lab Submission and Marking

Each lab exercise must be submitted using the give command or via give's web interface by 5pm Monday (Sydney time) in the week following the lab. Multiple submissions are allowed - only the last submission will be marked. Late submissions will be penalised in accordance with UNSW's standard late penalty (see below).

Each lab exercise will be marked out of 5. Marks for each lab consist of an automarking component, which is based on the correctness of the code, and a handmarking component, which is based on other aspects such as style and complexity analysis. The weightings of these components vary depending on the lab. Specific details can be found in the specification for each lab.

Labs that have an automarking component will be automarked after submissions are closed. Marks for the handmarking component can be obtained by showing your work to your tutor during your lab session, within two weeks of the lab. You must show the work that you submitted, not a modified version of your work or someone else's work. Your tutor will provide feedback on your approach to the problem and on the style of your solution.

Your final lab mark will be made up of the best 7 labs, with the lowest mark being discarded. For example, if your scores for the labs are 2/5, 3/5, 3/5, 4/5, 4/5, 4/5, 5/5 and 5/5, then the 2/5 would be discarded, and your final percentage for the labs would be 28/35 = 80%.

Quizzes

At the beginning of each week (except Weeks 6 and 10), a quiz will be released on WebCMS which tests your understanding of the lecture content from that week and the week prior. Quizzes are to be completed individually.

Quizzes must be submitted by 5pm Monday (Sydney time) two weeks after the quiz is released. Multiple submissions are allowed - only the last submission will be marked. Late submissions will be penalised in accordance with UNSW's standard late penalty (see below).

Each quiz will be marked out of 8. Your final quiz mark will be made up of the best 7 quizzes, with the lowest mark being discarded. For example, if your scores for the quizzes were 5/8, 5/8, 6/8, 7/8, 7/8, 7/8, 7/8 and 8/8, then one of the 5/8's would be discarded, and your final percentage for the quizzes would be 47/56 = 83.9%.

Assignments

There are two assessable programming assignments.

In the assignments, you will work on more substantial (hundreds of lines of code) programming exercises. Assignments give you the chance to practice that you have learned on relatively large problems. Assignments are a very important part of this course, therefore it is essential that you attempt them yourself. Collaboration with other students is limited to discussion of fundamentals, not any discussion of assignment specifics. All assignments are thoroughly checked for plagiarism, which can result in serious academic consequences.

Late submissions will be penalised in accordance with UNSW's standard late penalty (see below).

Final Exam

There will be a three-hour final exam, held in the CSE labs during the exam period.

The final exam is a summative assessment that will test your understanding of concepts covered in the course and your programming ability. The exam will contain short-answer questions and programming questions. A sample exam will be provided in Week 10 to demonstrate the format of the exam.

Fit-to-Sit Policy

UNSW has a fit-to-sit policy, which means if you sit the final exam, you are declaring yourself fit enough (both physically and mentally) to complete the exam to the best of your ability. Supplementary exams will only be granted to students that are granted Special Consideration.

Assessment

Your final mark in this course will be based on components from the assignment work, quizzes, labs, and the final exam.

Item Topics Due Marks Contributes to CLO
Labs All topics Weeks 1, 2, 3, 4, 5, 7, 8, 9 15% 1, 3, 4, 5
Quizzes All topics Weeks 2, 3, 4, 5, 7, 8, 9, 10 10% 1, 2, 3, 4, 5, 6, 7
Assignment 1 Trees Week 7 15% 4, 5, 7, 8
Assignment 2 Graphs Week 10 20% 4, 5, 7, 8
Final Exam All topics Exam period 40% 1, 2, 3, 4, 5, 6, 7, 8

To pass the course you must achieve a minimum (scaled) mark of 50% in the final exam.

The following describes precisely how your final mark will be computed:

labs                = mark for lab exercises         (out of 15)
quizzes             = mark for quizzes               (out of 10)
ass1                = mark for assignment 1          (out of 15)
ass2                = mark for assignment 2          (out of 20)
finalExam           = mark for final exam            (out of 40)
bonus               = bonus marks
mark      = labs + quizzes + ass1 + ass2 + finalExam + bonus
okHurdle  = finalExam >= 20
grade     = HD|DN|CR|PS  if mark >= 50 and okHurdle
          = FL           if mark <  50
          = UF           if mark >= 50 and !okHurdle

Late Penalties

COMP2521 implements UNSW's standard late submission penalty, described here . Late submissions for lab exercises, quizzes and assignments will be penalised by 0.2% of the maximum mark per hour or part thereof, deducted from the attained mark ( not the maximum mark), capped at five days from the assessment deadline, after which submissions are no longer accepted.

For example, a submission worth 91% that is submitted 10 hours late will receive a penalty of 2%, resulting in a mark of 89%. A submission worth 91% that is submitted 25 hours late will receive a penalty of 5%, resulting in a mark of 86%.

Technical Issues and Extensions

Extensions will only be given if there is scheduled server maintenance or servers unexpectedly go down close to the deadline. Please make sure to start your lab exercises and assignments early and work on them consistently.

Special Consideration

If your work in this course is affected by unforseen adverse circumstances, you should apply for Special Consideration through myUNSW, including documentation on how you have been affected. If your request is reasonable and your work has clearly been impacted, then:

  • For a lab exercise/quiz/assignment, you may be granted an extension
  • For the final exam, you may be offered a supplementary exam

Note that an extension is not immediately guaranteed upon applying for Special Consideration - whether you are granted an extension depends on whether you make a convincing case that the circumstances have clearly impacted your ability to work.

If you are registered with Equitable Learning Services, please forward your Equitable Learning Plan to the course email address within the first two weeks of the term.

Course Schedule

Please note that this course schedule is just a plan and is subject to change.

Week Lectures Tutorials Labs Assignments
1 Introduction, Linked List Revision, Recursion Welcome, COMP1511 Recap Linked Lists -
2 Analysis of Algorithms, Abstract Data Types (ADTs) Compilation & Makefiles, Recursion Linked Lists, Arrays, ADTs -
3 Binary Search Trees Analysis of Algorithms Analysis of Algorithms
4 AVL Trees, 2-3-4 Trees Binary Search Trees Binary Search Trees Assignment 1 released (Tuesday lecture)
5 Graph Basics, Graph Traversal, Graph Algorithms AVL Trees, 2-3-4 Trees, Graph Basics Graph Basics -
6 No lectures No tutorials No labs -
7 Directed/Weighted Graphs, Minimum Spanning Trees (MSTs), Dijkstra's Algorithm Graph Traversal, Graph Algorithms Graph Traversal Assignment 1 due (Monday 5pm)
Assignment 2 released (Tuesday lecture)
8 Sorting Algorithms Directed/Weighted Graphs, MSTs, Dijkstra's Algorithm MSTs -
9 Heaps, Priority Queues, Hashing, Tries Sorting Algorithms Sorting Algorithms -
10 Course Review, Exam Details Heaps, Hashing, Tries Assignment 2 due (Friday 5pm 8pm)

Resources for Students

Forum

The course forum is a resource where students can ask questions to clarify their understanding of the course material and increase their knowledge, share helpful resources and insights, and ask for debugging help.

Student participation is encouraged. Up to 3 bonus course marks can be awarded for making good contributions to the forum, such as answering other students' questions well, explaining a concept well, and sharing helpful resources.

Textbooks

You are not required to purchase any additional materials. Some students have found the resources below to be useful in the past.

COMP2521 follows the contents of the pair of books:

  • Algorithms in C, Parts 1-4: Fundamentals, Data Structures, Sorting, Searching (3rd Edition)
    by Robert Sedgewick, published by Addison-Wesley
  • Algorithms in C, Part 5: Graph Algorithms (3rd Edition)
    by Robert Sedgewick, published by Addison Wesley

These two books are available as a bundle from the UNSW bookshop. They are expensive, but are useful well beyond this course, and will serve as a useful reference on the bookshelf of any serious programmer.

You may also be able to find on-line resources related to the textbooks. Robert Sedgewick has a series of videos on the topics in this course, but unfortunately they all seem to be in Java (which he has used for the new edition of his book). If you find any useful on-line resources, please let me know and we will add them to the Resources section of the course web site (with credit to the finder).

We will also use examples from the following book.

  • Introduction to Algorithms (Fourth Edition)
    by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein

The book has a large number of practice exercises.

This website also has links to the auxiliary material/documentation that you will need for the course. Solutions for all tutorial questions and lab exercises will also be made available.

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 of Conduct as discriminatory, sexually inappropriate, bullying, harassing, invading another'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 , the School Grievance Officer , or one of the student representatives .

Plagiarism

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.

[What follows is courtesy of Stuart Prescott in Chem Eng ...]

Artificial intelligence tools such as ChatGPT, CodePilot, CoPilot, and built-in functions within Word are modern tools that are useful in some circumstances, but reliance on them is not a path to success at university or in your later career. Reaching for a calculator to add up 1+1 is possible but not professionally sustainable for an engineer or scientist (or one might say in our educated society at all!), and that is why you learnt to do that yourself at primary school. Likewise, in your degree at UNSW, we're teaching you skills that are needed for your professional life, which is a combination of some things that AI could feasibly do for you and lots of things that the AI tools cannot do for you ? if we were only teaching you things that AI could do, your degree would be worthless and you wouldn't have a job in 5 years. You can therefore see that from an academic standards perspective, the output from an AI tool will be below the minimum standards expected for a course, even if you were to submit it (which you should not!). Your ability to complete later assessments where AI cannot help you will also be compromised if you've relied upon AI earlier.

It is also worth remembering what these AI tools such as ChatGPT are: they are only statistical models about how groups of words frequently appear. These AI based tools are not smart, they don't know anything other than how words are often grouped, and they most certainly do not understand any of the content from any of your courses. Some consequences of their word-statistics and non-scientific basis are:

  • They generate confident-sounding text that is completely wrong from a technical point of view.
  • The text mangles jargon very badly.
  • The output gets causality backwards and so often argues completely the wrong thing.
  • The output will include unit conversions but it will often get them wrong.
  • The generated text is often very generic, bland, lacking on detail, and not actually very helpful.
  • The output is often just a collection of loosely related factual-sounding sentences that don't answer the question that was actually asked.
  • In summary, the AI tools generate text output that is superficially reasonable, very confident sounding, and very often wrong. We are setting an expectation that our graduates should out-perform AI, meaning that it is a tool of limited academic use in your degree.

[Thanks Stuart]

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:

Use of Generative Tools in COMP2521

Systems such as GitHub Copilot and ChatGPT based on large language models or other generative artificial intelligence techniques, look likely to become heavily used by programmers.

However, you need a good understanding of the language you are coding in and the systems involved before you can effectively use these tools.

Using these tools to generate code for COMP2521 instead of writing the code yourself will hinder your learning.

You are not permitted to submit code generated by automatic tools such as GitHub Copilot, ChatGPT, Google Bard in COMP2521 including for lab exercises and assignments.

Submitting code generated by GitHub Copilot, ChatGPT, Google Bard and similar tools will be treated as plagiarism.

These automatic tools will not be available in the exam environment.

Referencing Code

In labs and assignments, any code you use that was copied or derived from anyone other than yourself must be clearly referenced. A simple guide for referencing code can be found here .

Course Evaluation and Development

Student feedback on this course, and on the effectiveness of lectures, tutorials and labs in this course, is obtained via electronic survey (myExperience) at the end of each semester. Student feedback is taken seriously, and continual improvements are made to the course based in part on this feedback. Students are strongly encouraged to let the lecturer in charge know of any problems as soon as they arise. Suggestions and criticisms will be listened to openly, and every action will be taken to correct any issue or improve the students' learning experience.

  • Structure and approach from 21T2: Following the feedback from 23T1, students tended to prefer the topic structure and depth presented in 21T2. Knowing this, we will use the approach from 21T2.

Happy learning!

Resource created Thursday 18 May 2023, 02:31:48 PM, last modified Thursday 03 August 2023, 09:43:29 PM.


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