Students

COMP2010 – Algorithms and Data Structures

2021 – Session 1, Special circumstances

Notice

As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group activities on campus, and most will keep an online version available to those students unable to return or those who choose to continue their studies online.

To check the availability of face-to-face and online activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Convenor
Annabelle McIver
Lecturer
Mark Dras
Credit points Credit points
10
Prerequisites Prerequisites
(COMP1010 or COMP125) and 10cp from (MATH132-MATH136 or DMTH137 or MATH1007-MATH1025 or (STAT150 or STAT1250) or (STAT170 or STAT1170) or (STAT171 or STAT1371) or (STAT175 or STAT1175))
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit provides a study of algorithms, data structures and programming techniques. The topics covered include: trees; graphs and heaps; advanced sorting techniques; elements of storage management; and complexity. The presentation emphasises the role of data abstraction and correctness proofs.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://students.mq.edu.au/important-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • ULO3: Apply commonly used data structures, including trees, graphs, lists and their variations.
  • ULO2: Apply strategies for achieving correctness in a range of algorithms.
  • ULO4: Carry-out advanced and broadly based problem solving, particularly when designing and writing programs to meet a given specification.
  • ULO5: Describe the results of analysing algorithms.

General Assessment Information

Standards and Grading

 The final mark for the unit will be calculated by combining the marks for all assessment tasks according to the percentage weightings shown in the assessment summary. 

Late Submission

No extensions will be granted without an approved application for Special Consideration. There will be a deduction of 20% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late. For example, 25 hours late in submission for an assignment worth 10 marks – 40% penalty or 4 marks deducted from the total.  No submission will be accepted after solutions have been posted.

Extension requests 

Please note if you cannot submit on time because of illness or other circumstances, please contact the lecturer before the due date. If you experience a disruption to studies, you should notify the university.  Please note that this is a centralised process, and resolution can take some time.  This may mean, for example, that you are notified that your disruption request has been approved only after any reasonable length extension for an assignment could be granted: for instance, the assignment might have already been handed back.  With respect to assignments, you should therefore also notify the lecturer responsible for the assignment, and submit a solution to the assignment via iLearn, at the same time as you lodge your official disruption notification.  Failure to do so means that an extension may not be possible, leaving only some other remedy listed under the disruption to study outcomes schedule (e.g. partake in assessment task next available session).

Special Consideration

If you receive special consideration for the final exam, a supplementary exam will be scheduled in the interval between the regular exam period and the start of the next session.  By making a special consideration application for the final exam you are declaring yourself available for a resit during the supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments.  Please ensure you are familiar with the policy prior to submitting an application. You can check the supplementary exam information page on FSE101 in iLearn (bit.ly/FSESupp) for dates, and approved applicants will receive an individual notification one week prior to the exam with the exact date and time of their supplementary examination.

 Summary of achievement required corresponding to each final grade

  • HD and D   Overall the quality of the work demonstrates a mature and considered appreciation of the programming and algorithmic concepts, and an excellent technical mastery of Java programming (sufficient to complete the advanced programming tasks). A systematic demonstration of the ability to problem solve independently and a thorough knowledge of how to critique the proposed solution, in terms of performance, correctness and other technical issues.
  • Cr   Overall the quality of the work demonstrates a reasonable appreciation of the programming and algorithmic concepts, and a good technical mastery of Java programming (sufficient to complete the required programming tasks). A systematic demonstration of the ability to solve basic problems and to present the solutions clearly with an attempt to give reasons why they meet their stated objectives. Some knowledge of how to critique the proposed solution, in terms of performance, correctness and other technical issues is demonstrated, but the answers given might not cover all cases.
  • P   The quality of work demonstrates a basic technical mastery of the Java language, a basic understanding of how to program using the studied algorithms and a knowledge of how to implement and use the basic algorithmic data structures and programming techniques introduced in the course. The assessment work demonstrates a basic understanding of performance and correctness issues relative to all of the algorithms and data structures studied in the unit, and the appropriateness of a particular algorithm relative to a given data structure.

Assessment Tasks

Name Weighting Hurdle Due
Assignment One 15% No Week 8
Final Exam 45% No Examination period
Weekly Exercises 5% No Weeks 2--13
Contribution to Learning 5% No Weeks 2--8
Assignment Two 20% No Week 12
Mid semester test 10% No Week 10

Assignment One

Assessment Type 1: Programming Task
Indicative Time on Task 2: 10 hours
Due: Week 8
Weighting: 15%

 

In this assignment you will be asked to design and analyse an algorithm based on material studied in weeks 1--5. Your algorithm will be implemented in the Java programming language using some of the design techniques taught in lectures and the weekly exercises. The focus is on correctness and the ability to write programs on list or tree data structures.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.

Final Exam

Assessment Type 1: Examination
Indicative Time on Task 2: 13 hours
Due: Examination period
Weighting: 45%

 

A formal written examination based on lectures, class work, activities, and assignments.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.
  • Carry-out advanced and broadly based problem solving, particularly when designing and writing programs to meet a given specification.
  • Describe the results of analysing algorithms.

Weekly Exercises

Assessment Type 1: Programming Task
Indicative Time on Task 2: 12 hours
Due: Weeks 2--13
Weighting: 5%

 

Each week you will be asked to submit the solutions to problems based on lecture material.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.
  • Carry-out advanced and broadly based problem solving, particularly when designing and writing programs to meet a given specification.

Contribution to Learning

Assessment Type 1: Participatory task
Indicative Time on Task 2: 0 hours
Due: Weeks 2--8
Weighting: 5%

 

The participation assessment encourages active and consistent engagement in COMP2010 content. There are two ways to obtain marks. (a) Attend a weekly workshop and complete additional participation exercises (0.5 mark from the tutor at the workshop). (b) Good citizenship eg consistent posting useful comments and contributions related to the material on the forum. Only tutors may nominate students for good citizenship participation (b), and the lecturers will be happy to consider such nominations.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.
  • Carry-out advanced and broadly based problem solving, particularly when designing and writing programs to meet a given specification.
  • Describe the results of analysing algorithms.

Assignment Two

Assessment Type 1: Programming Task
Indicative Time on Task 2: 20 hours
Due: Week 12
Weighting: 20%

 

You will be asked to design and implement an algorithm in Java based on graph data structures using some of the more advanced techniques discussed in lectures.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.

Mid semester test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 10 hours
Due: Week 10
Weighting: 10%

 

Mid semester test based on tutorial questions in weeks 1--9. This will be delivered as an iLearn Quiz.

 


On successful completion you will be able to:
  • Demonstrate an understanding of a variety of algorithm design techniques and how they can improve either efficiency or clarity.
  • Apply commonly used data structures, including trees, graphs, lists and their variations.
  • Apply strategies for achieving correctness in a range of algorithms.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Learning Skills Unit for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Technology required

  • Eclipse - download Eclipse IDE for Java Developers: The practical work in this unit involves programming in Java (www.java.com) using the Eclipse Integrated Development Environment (www.eclipse.org)
  • Java SE JDK - download Java SE 8 to be compatible with the labs: Note that you need the Java JDK which includes the compiler tools, rather than the Java Runtime Environment (JRE) which you might already have installed on your computer to allow you to run Java applications.
  • Any additional Java libraries will be made available for download.
  • Learning Management System iLearn : This will be used primarily to enable email broadcasts and give access to Assessment marks.
  • The lecture audio will be recorded, and will be available via iLearn.

Classes

Each week you should attend 2 hours of lectures and a two-hour mixed classes. For details of days, times and rooms consult the timetables webpage.

You should have selected one two-hour mixed classes session at enrolment. You must attend the session you are enrolled in.

Please note that you are expected to attend most of the mixed classes because that is your opportunity to seek clarification of any parts of the course and exercises you do not understand. Note that the in-class quiz will be strongly based on the weekly exercises. You are therefore strongly advised to complete the set class exercises, and to seek clarification when you are unable to complete a question.

Recommended Texts

The following texts can be used to supplement the material covered in lectures:

Robert Sedgewick and Kevin Wayne.  Algorithms (4th edition) - available online at https://algs4.cs.princeton.edu/home/

Clifford Shaffer. Data Structures and Algorithm Analysis - available online at https://people.cs.vt.edu/shaffer/Book/JAVA3e20130328.pdf

Adam Drozdek [2005]. Data Structures and Algorithms in Java (2nd ed. or 3rd edition). Boston: Thomson Course Technology.

There is also a companion website by the publisher, containing data files for exercises. In addition, Drozdek has Java code from the book available on his webpage. (Note that these are written for Java 1.4.)

Unit Pages

The unit will make use of discussions hosted within iLearn. Please post questions there, they will be monitored by the staff on the unit.

Teaching and Learning Strategy

COMP2010 is taught via lectures and mixed classes in the laboratory. Lectures are used to introduce new theoretic material, give examples of the use these techniques and put them in a wider context. Mixed classes give you the opportunity to interact with your peers. You will be given problems to solve each week prior to each session; preparing solutions is important because it will allow you to discuss the problems effectively with your tutor thereby making the most of this activity. The aim of the mixed classes is to help you to develop problem-solving skills and teamwork, and you will be expected to work on problems in class. Mixed classes give you an opportunity to practice your programming skills, and to implement many of the ideas discussed in lectures. Each week you will be given a number of problems to work on; it is important that you keep up with these problems as doing so will help you understand the material in the unit and prepare you for the work in assignments and quizzes. Some of the questions are designated priority and they will be the ones that will be discussed in detail and on which the quizzes may be based. Additional questions are provided for extension and general practice.

There will be an opportunity to explore more deeply aspects of the course material which has not been covered in lectures or classes. These will sometimes be student-led, and in various forms including Q&A with the lecturer or short videos. Topics will for example include questions not covered in workshops, or hints and tips for assignments. More information for the timing of these sessions will be available on iLearn.

Lecture notes will be made available each week but these notes are intended as an outline of the lecture only and are not a substitute for your own notes or the textbook.

Unit Schedule

Week 1 Review of algorithms and related concepts
Week 2 Algorithm Correctness and Efficiency
Week 3 Algorithm Design Strategies
Week 4 Sorting
Week 5 Binary Trees
Week 6 Binary Trees (cont.)
5--18 April

Mid semester break

Week 7l

Priority Queues, Heaps and Heapsort

Week 8 Programming with Maps and Hashtables
Week 9 Graph Algorithms
Week 10 Graph Algorithms (cont.)
Week 11 Advanced Trees
Week 12 An Introduction to Computability
Week 13

Revision

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Enquiry Service

For all student enquiries, visit Student Connect at ask.mq.edu.au

If you are a Global MBA student contact globalmba.support@mq.edu.au

Equity Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.