COMP2521 19T2
Course Outline


Course Details

Course Code
Course Name
Data Structures and Algorithms
Units of Credit
Course Convenor
Ashesh Mahidadia <>
Course Website
Handbook Entry

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 lectres, tutorials, lab classes, and assignments. Assessment involves labs, tutes, practical lab exams, a practical final exam, and a theory exam. 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, capable of building significant software systems in a team environment, and ready to continue with further specialised studies in computing.

Topics: An introduction the structure, analysis and usage of a range of fundamental data types and the core algorithms that operate on them, including: algorithm analysis, sorting, searching, trees, graphs, files, algorithmic strategies, analysis and measurement of programs. Labs and programming assignments in C, using a range of Unix tools.

Executive Summary

A summary of the critical things to know about COMP2521:

Now, please read the rest of this document.

Course Timetable

The complete course timetable is available at: webcms3:/timetable

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, is this piece of software any good? 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.

Student Learning Outcomes

After completing this course, students will:

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 blog, 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

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:

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

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. Tutorials aim 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, assignments and a text book.

Lectures aim to convey basic information about the course content and to model the practices and techniques involved in software development (i.e., we do demos). 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 text book and notes. Labs and assignments are where you get to put together and practise all of the ideas from the lectures, tutes and text. 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. An 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 learningtool, 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.


Each week there will be three hours of lectures during which theory, practical demonstrations and case-studies 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. Feel free to ask questions at any stage, but otherwise please respect the right of other people around you who are trying to listen and (shhhhhh!) keep quiet.

Note that we may not post the lecture slides before the lecture, to encourage you to concentrate on the fresh material! However, the lecture topics are available in the course outline.

Text vs Slides


Tutorials aim to clarify ideas from lectures and to get you to think about design/analysis issues. There will be a number of exercises set for each tutorial class. 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. Ideally, students should run the entire tute themselves, with the tutor being a moderator and occasionally providing additional explanations or clarifications.

Lab Classes

Lab classes aim to give you practice in problem-solving and program development. Each week, there will be one or two small exercises to work on. These exercises will be released in the week preceding the lab class. Labs will be done in pairs, and you and you partner should discuss the exercises before going to the lab, to maximise the usefulness of the class. The exercises will need to be submitted (for our records) and will be assessed by your tutor. During the lab, your tutor will provide feedback on your approach to the problem and on the style of your solution.

Pairs will also be asked to do code reviews in the tutorials, to explain how they tackled a particular problem and describe interesting features of their solution.


In the assignments, you will work on more substantial (hundreds of lines of code) programming exercises. The first assignment is an individual assignment; the second will be completed in groups. We expect all members of a pair or group to contribute to the assignments; part of your assignment mark will be tied to this. As noted above, assignments are the primary vehicle for learning the material in this course. If you don't do them, or simply copy and submit someone else's work, you have wasted a valuable learning opportunity.


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

Note that the exam is a hurdle, so that if you fail the exam badly enough, you cannot pass the course. If your failure in the exam is due solely to failing the Prac part, and the rest of your marks are satisfactory (okEffort), you will be given a second chance to complete the Prac.

The following formula describes precisely how the mark will be computed and how the hurdle will be enforced:

labs                = mark for lab exercises         (out of  8)
ass1                = mark for assignment 1          (out of  8)
ass2                = mark for assignment 2          (out of 14)
midterm             = mark for midterm exam          (out of 10)
finalExam           = finalPracExam (36)
                    + finalTheoryExam (24)           (out of 60)

okHurdle            = (finalPracExam + midterm) > 23

assignmentMarks     = ass1 + ass2
assPerc             = assignmentMarks in percentages (out of 100)
pracExamPerc        = finalPracExam in percentages (out of 100)
if (assPerc > pracExamPerc) {
    // harmonic mean of assPerc and pracExamPerc
    adjusted_assPerc = (2 * assPerc * pracExamPerc) / (assPerc + pracExamPerc)
    assignmentMarks  = 22 * (adjusted_assPerc / 100)

mark      = labs + assignmentMarks + practicalLabExams + finalExam
grade     = HD|DN|CR|PS  if mark >= 50 && okHurdle
          = FL           if mark <  50
          = UF           if mark >= 50 && !okHurdle

In other words, if you don't learn how to program by doing the prac work yourself, you'll score poorly in the final prac exam, resulting in reduced assignment marks and making it very difficult for you to pass the course.

For more clarification on adjusted_assPerc (or why you should do the prac work yourself!), see the following table:

Course Schedule

The schedule of lecture topics (subject to change) is:

Week Topics
1 Introduction to the course, C vs COMP1511 vs COMP2521
Analysis of Algorithms
2 Analysis of ADT (multiple) implementations
Trees, Binary Search Trees (BST)
3 Balanced Trees, Search Tree Algorithms
4 Graph ADT, Graph Algorithms (1)
5 Graph Algorithms (2)
6 Hashing, Heaps
During your lab time: Mid-term exam
7 Generic ADTs in C
Sorting (1)
8 Sorting (2)
9 Text processing algorithms
10 Course Review and Review Exercises

Tutorial/Laboratories: Each topic will be dealt with in tutes/labs in the week after it is covered in lectures.

Supplementary Exams

The document "Essential Advice for CSE Students" states the supplementary assessment policy for the School of CSE. Please take the time to read it carefully.

If you are granted a Supplementary examination, then it will be centrally timetabled. If you think that you may be eligible for a supplementary exam, then make sure you are available on that day. It is your responsibility to check at the Student Office for details of Supplementary examinations.

Please note that there will be NO further supplementary dates for this course. In other words, we will NOT be able to offer you supplementary examination at any other time.

Resources for Students

COMP2521 follows the contents of the pair of books:

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 text books. 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).

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. We will review quiz and assignment solutions in the lectures.

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'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 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:

Course Evaluation and Development

Student feedback on this course, and on the effectiveness of lectures 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.