COMP9201: Semester 2, 2021

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Units COMP9201 Semester 2 2021 [Normal day]

Unit of study_

COMP9201: Software Construction and Design 1

Semester 2, 2021 [Normal day] - Remote

Overview

This unit introduces the foundations of software design and construction. It covers the topics of modelling software (UML, CRC, use cases), software design principles, object-oriented programming theory (inheritance, polymorphism, dynamic subtyping and generics), and simple design patterns. The unit aims to foster a strong technical understanding of the underlying software design and construction theory (delivered in the lecture) but also has a strong emphasis of the practice, where students apply the theory on practical examples.

Unit details and rules

Unit code	COMP9201
Academic unit	Computer Science
Credit points	6
Prohibitions ?	INFO3220 OR SOFT2201
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	COMP9103 (or equivalent UoS at a different institution)
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ying Zhou, ying.zhou@sydney.edu.au
Lecturer(s)	Martin McGrane, martin.mcgrane@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Take-home short release)	Final exam Online Final Exam	50%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Software construction stage 1 * UML Assignment	5%	Week 05	n/a
Outcomes assessed:
Assignment	Software construction stage 2 * Design Pattern Assignment	15%	Week 08	n/a
Outcomes assessed:
Assignment	Software construction stage 3 * Design Pattern Assignment	20%	Week 12	n/a
Outcomes assessed:
Assignment	Weekly Exercises * submission on canvas from week 1 to week 12	10%	Weekly	n/a
Outcomes assessed:
= hurdle task ? = Type D final exam ?

Assessment summary

* indicates an assessment which must be repeated if a student misses it due to special consideration.
Weekly Exercise: it will cover the lecture/tutorial from the current week.
There may be statistically defensible moderation when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

Minimum Pass Requirement

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the final examination. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to software construction and design	Lecture and tutorial (4 hr)
Week 02	OO theory 1: Java knowledge revisited	Lecture and tutorial (4 hr)
Week 03	UML&Software modelling case studies	Lecture and tutorial (4 hr)
Week 04	OO theory 2: software design principles and design smells	Lecture and tutorial (4 hr)
Week 05	Design pattern 1	Lecture and tutorial (4 hr)
Week 06	Design pattern 2	Lecture and tutorial (4 hr)
Week 07	Testing	Lecture and tutorial (4 hr)
Week 09	Code review	Lecture and tutorial (4 hr)
Week 10	Design pattern 3	Lecture and tutorial (4 hr)
Week 11	Design pattern 4	Lecture and tutorial (4 hr)
Week 12	Design pattern 5	Lecture and tutorial (4 hr)
Week 13	Unit review	Lecture and tutorial (4 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Craig Larman, Applying UML and Patterns (3rd). Pearson.
Gamma, Helm, Johnson, Vlissides, Design Patterns: Elements of Reusable Object-Oriented Software. Addison Wesley, 2004. 9780201633610.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. explain processes and elements in object-oriented design
LO2. apply object-oriented design approaches to software design
LO3. apply object-oriented design principles to implementation using an OO programming language
LO4. object oriented theory including inheritance, polymorphism, dynamic binding, subtyping and generics
LO5. discuss and apply basic testing techniques and code review to software systems

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Adjustment of assignment content and due dates.

Additional information

Knowledge of OO theory and Java programming is required

IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.Inassessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the MOSS similarity detection engine (see http://theory.stanford.edu/~aiken/moss/), or the similarity report available in ED (edstem.org). These programs work in a similar way to TurnItIn in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.

All written assignments submitted in this unit of study will be submitted to the similarity detecting software program known as Turnitin. Turnitin searches for matches between text in your written assessment task and text sourced from the Internet, published works and assignments that have previously been submitted to Turnitin for analysis.There will always be some degree of text-matching when using Turnitin. Text-matching may occur in use of direct quotations, technical terms and phrases, or the listing of bibliographic material. This does not mean you will automatically be accused of academic dishonesty or plagiarism, although Turnitin reports may be used as evidence in academic dishonesty and plagiarism decision-making processes.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

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