COMP7000 will be assessed and graded according to the University assessment and grading policies.

Submission Deadlines

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 7^th day (including weekends). After the 7^th 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 a technical concern.

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. 

Assessments where Late Submissions will be accepted: allSpecial 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 ask.mq.edu.au.

Standards

The following general standards of achievement will be used to assess each of the assessment tasks with respect to the letter grades. 

Pass: Has a basic understanding of the algorithms and concepts as discussed in class. Can  describe and reproduce definitions and fundamental algorithms. Can perform a basic research investigation in the area and present the results of that research in rudimentary written and oral forms.

Credit: As for Pass plus: Is able to apply the algorithmic techniques we have discussed to derive solutions to computational problems. Can develop, generalise and apply the concepts discussed in class to address basic theoretical and practical questions, and can effectively communicate these insights. Shows more than basic insights into the results of a research investigation and is able to communicate those insights.

Distinction/High Distinction: As for Credit plus: Is able to generalise and synthesise knowledge to address more complex topics beyond the material discussed in class. Can critically evaluate the limits of the techniques and algorithms discussed.

Assessment Process

These assessment standards will be used to give a numeric mark out of 100 to each assessment submission during marking. The mark will correspond to a letter grade for that task according to the University guidelines. The final raw 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%.

Projects

Assessment Type ¹: Project Indicative Time on Task ²: 40 hours Due: Weeks 1 -- 12 Weighting: 54%

Students will be asked to complete 4 projects. These will consist of a combination of programming, program analysis and report writing.

On successful completion you will be able to:

• Explain key ideas in the field of algorithmics and the workings of key algorithms, and compare and evaluate algorithmic solutions for computational problems.
• Formally analyse algorithms.
• Implement key algorithms.
• Develop algorithmic solutions for computational problems by constructing new algorithms and combining existing algorithms.

Presentation

Assessment Type ¹: Presentation Indicative Time on Task ²: 10 hours Due: Week 12-13 Weighting: 10%

An oral presentation supported by appropriate presentation materials.

On successful completion you will be able to:

• Explain key ideas in the field of algorithmics and the workings of key algorithms, and compare and evaluate algorithmic solutions for computational problems.
• Investigate topics in advanced algorithms and synthesise the output for presentation in oral and written form.

Weekly tasks

Assessment Type ¹: Problem set Indicative Time on Task ²: 0 hours Due: Weeks 1--12 Weighting: 36%

Each week students will be asked to complete some exercises to test their understanding of the material.

On successful completion you will be able to:

• Explain key ideas in the field of algorithmics and the workings of key algorithms, and compare and evaluate algorithmic solutions for computational problems.
• Formally analyse algorithms.
• Implement key algorithms.
• Develop algorithmic solutions for computational problems by constructing new algorithms and combining existing algorithms.
• Investigate topics in advanced algorithms and synthesise the output for presentation in oral and written form.

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

Classes

Each week has two hours of face-to-face class. These classes will be a mixture lecture material, discussion and in class tests.

Recommended Reading and References

There is no set text for the course, but the following far from exhaustive list of texts may be useful for reference, study and further reading:

• Skiena, Algorithm Design Manual, Spinger.
• Cormen, Leiserson, Rivest and Stein.  Introductions to algorithms, Prentice Hall.
• Papadimitriou, Computational Complexity, Addison Wesley.
• Sipser, Introduction to the Theory of Computation, Thomson.

Unit Webpage, Materials and Technologies Used

The materials for the unit including notes, discussion fora, electronic submission links etc. will be through the iLearn system.

The programming projects can be done in any programming language subject to prior approval of the course convener.  Languages can include Java and Python.