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. Requirements to Pass this Unit To pass this unit you must achieve a total mark equal to or greater than 50%. There is no hurdle. Weekly Exercises Weekly exercises are for practice and are neither assessed nor marked. Release Assignment 1 should be release no later than end of week 2 (Sunday 10 August). Assignment 2 should be release no later than end of week 8 (Sunday 21 September). Late Assessment Submission Penalty Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience technical concerns. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/ presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration. For example, if the assignment is worth 8 marks (of the entire unit) and your submission is late by 19 hours (or 23 hours 59 minutes 59 seconds), 0.4 marks (5% of 8 marks) will be deducted. If your submission is late by 24 hours (or 47 hours 59 minutes 59 seconds), 0.8 marks (10% of 8 marks) will be deducted, and so on.

There will be two assignments that assess students' ability to design, implement and understand the algorithms covered during the session. On successful completion you will be able to: • Solve concrete problems and provide adapted algorithmic solutions using advanced algorithmic knowledge. • Design and implement algorithms to satisfy specified problem constraints. • Communicate clearly and effectively the relevant aspects of algorithms and their performance. • Work collaboratively in a small team to design and implement advanced algorithms. 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 Writing Centre 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.

Special Consideration The Special Consideration Policy aims to support students who have been impacted by short- term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through http://connect.mq.edu.au/.

Assignment 1 Assessment Type 1: Project Indicative Time on Task 2: 30 hours Due: Sunday 14 September 2025 Weighting: 30%

This assignment assesses students' ability to design, implement and understand algorithm strategies covered during the first 4 weeks.

On successful completion you will be able to: • Solve concrete problems and provide adapted algorithmic solutions using advanced algorithmic knowledge. • Design and implement algorithms to satisfy specified problem constraints. • Communicate clearly and effectively the relevant aspects of algorithms and their performance. • Work collaboratively in a small team to design and implement advanced algorithms.

Assignment 2 Assessment Type 1: Project Indicative Time on Task 2: 30 hours Due: Sunday 2 November 2025 Weighting: 30%

This assignment assesses students' ability to design, implement and understand algorithm strategies covered during the second part of the unit.

On successful completion you will be able to: • Solve concrete problems and provide adapted algorithmic solutions using advanced algorithmic knowledge. • Design and implement algorithms to satisfy specified problem constraints. • Communicate clearly and effectively the relevant aspects of algorithms and their performance. • Work collaboratively in a small team to design and implement advanced algorithms.

Final Examination Assessment Type 1: Examination Indicative Time on Task 2: 20 hours Due: Exam Period (weeks 14-16) Weighting: 40%

The final examination will be a written examination held during the usual University examination period and will cover all topics. On successful completion you will be able to: • Solve concrete problems and provide adapted algorithmic solutions using advanced algorithmic knowledge. • Communicate clearly and effectively the relevant aspects of algorithms and their performance. 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 Writing Centre 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

Lectures start in week 1 but Workshops start in week 2 (there is NO workshop in week 1). 1. Classes Materials for COMP3010/6102 will be mainly presented through face-to-face lectures.

The lectures introduce the weekly topic at a more general level and present an opportunity to have live discussions on the content. Each week, there will also be a two-hour workshop class where you should attempt a set of questions based on the week's topic under the guidance of the tutor. The workshop also gives you a chance to discuss any course-related problem you may have with the tutor and your peers. An extra question will also be made available every week for individual practice (not assessed and not marked). It is important that you keep up with the problems in your workshop classes as doing so will help you understand the material in the unit and prepare you for your assignments, tests and final exam. 2. The following textbooks are not required for COMP3010, but are highly recommended as we will use them as the basis for most of the course. Both textbooks are available online via the library website. • (CLRS) T. H. Cormen, C. E. Leiserson, R. L. Rivest, & C. Stein, Introduction to Algorithms (MIT Press) 3rd edition. ISBN 0-262-53305-7. • (Skiena) S. S. Skiena, The Algorithm Design Manual, Springer, 2nd edition, 2008, ISBN: 978-1-84800-069-8

Technology The coding component for this course will be presented using the Java programming language as the recommended development environment. You may be expected to use git version control for parts of the course. Methods of Communication We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

Methods of Communication.

Our primary means of communication will be through your university email and announcements on iLearn. It is crucial to consistently check your university's email for important updates and information related to the course. The teaching staff will not entertain emails that do not originate from university email IDs. Additionally, significant announcements will be posted on iLearn, a centralized platform for accessing vital details about the course. Should you have any queries or require assistance from the teaching staff, including the unit convenor, you have two communication channels. Firstly, you can post your queries on the iLearn discussion board, providing an interactive space for instructors and peers to engage in discussions. Alternatively, you may send emails to the corresponding addresses of the teaching staff using your university email address for official communication. Through these communication methods, we aim to ensure effective and timely dissemination of information and provide the necessary support throughout the course.

Lectures start in Topics covered each week: 1. Introduction and Complexity Analysis 2. Algorithm Correctness 3. Asymptotic Notations 4. Greedy Algorithms 5. Divide & Conquer 6. Dynamic Programming 7. Probabilistic Algorithms 8. String algorithms 9. Graph Algorithms 10. Graph Algorithms (continued) 11. Continuing with graph algorithms 12. Reduction and comparing the hardness of problems 13. Revision

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page. The lecture sessions have been reduced from 3 to 2 hours. SGTAs will remain to allow to complete more exercises and prepare for the assessments. Number of assessments have been reduced to three as per University policy.