Outline

Overview

In this unit of study, elementary methods for developing robust, efficient, and re-usable software will be covered. The unit is taught in C, in a Unix environment. Specific coding topics include memory management, the pragmatic aspects of implementing data structures such as lists and hash tables and managing concurrent threads. Debugging tools and techniques are discussed and common programming errors are considered along with defensive programming techniques to avoid such errors. Emphasis is placed on using common Unix tools to manage aspects of the software construction process, such as version control and regression testing. The subject is taught from a practical viewpoint and it includes a considerable amount of programming practice.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	INFO1113 OR INFO1105 OR INFO1905 OR INFO1103
Corequisites ?	COMP2123 OR COMP2823 OR INFO1105 OR INFO1905
Prohibitions ?	COMP2129 OR COMP9017 OR COMP9129
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	John Stavrakakis, john.stavrakakis@sydney.edu.au
Tutor(s)	Tyson Thomas, tyson.thomas@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Take-home extended release)	Final examination Open book computer exam + closed book oral exam	50%	Formal exam period	48 hours
Outcomes assessed:
Assignment	Task set 1 Solve programming problems before the due date.	5%	Week 04 Due date: 18 Sep 2020 at 23:59	14 days
Outcomes assessed:
Assignment	Task set 2 Solve programming problems before the due date.	5%	Week 07 Due date: 16 Oct 2020 at 23:59	14 days
Outcomes assessed:
Assignment	Task set 3 Solve programming problems before the due date.	10%	Week 11 Due date: 15 May 2020 at 23:59	21 days
Outcomes assessed:
Assignment	Task set questions Answer questions on Task set 3 with tutor	5%	Week 12	15 minutes
Outcomes assessed:
Assignment	Weekly problem Complete programming exercise and answer questions from tutor.	25%	Weekly	7 days
Outcomes assessed:
= hurdle task ? = Type E final exam ?

Assessment summary

Weekly problem:
Weekly activities required to complete prior to the beginning of the tutorial class. Lectures and Tutorials are both included as part of the Lessons. Tutorial participation required to answer questions from tutor during tutorial as a part of the formative assessment.
Task set:
The task sets are a series of programming exercises to be completed throughout the semester. To be completed independently. These are released regularly and have varying submission dates. Late enrolments (up to week 4) will be able to submit prior weeks.
Task set questions:
Students will be assessed with their tutor for their task set 3 submission based on questions and answers similar to the Weekly problem. The session will be conducted in person or online after the submission of Task set 3.
Final examination:
The final exam covers all aspects of the course. Demonstrate knowledge in procedural programming. Reading and tracing through short programs. Writing short programs. Writing test cases and debugging with existing test cases. The final exam consists of a computer examination 34%, and an oral examination 66%.

The computer examination is an open book examination that will require at most 4 hours to complete. This will be made available in the first 3 days of the examinations week.

The oral examination will be administered in examinations week and will require working internet connection, video conferencing software (supported by University). The contents will examine the submitted open book examination.

Detailed information for each assessment can be found on the course website: edstem.org

Special consideration
Weekly problem - Approved special consideration will be granted an extension to complete the problem and may additionally be examined in an oral quiz online, based on their contents.
Task sets - Approved special consideration will be granted an extension to complete the task set and may additionally be examined in an oral quiz online, based on their contents.
Final examination – a replacement examination will be arranged, however the format may vary and further development may be required.

Conditions for pass in this course:
- At least 40% in the assessment grade
- At least 50% in the oral examination
- At least 50% in the computer examination
- At least 50% total

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 formative assessment and 40% in the final exam. 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.

Additionally for this course, any student not meeting the oral examination barrier of 50% will have their computer examination mark no more than the oral examination mark. Students may be asked for further development of their assessments if they fail to attend at least 80% of their tutorials.

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.

The tutor will provide feedback for the weekly problem during the tutorial.

Task sets require online submission by the due date for checking by teaching staff.

The tutors will provide further feedback to students about correctness, style and testing.

Automatically graded submissions provide further feedback.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late penalty for any online assessment is 25% per day. It is a cap based penalty: 1 day late, maximum attainable mark is 75%. 2 days late, maximum attainable mark is 50%. 3 days late, maximum attainable mark is 25%. Failure to attend for any assessment that requires attendance will award zero marks, unless special consideration is granted.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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	Admin/introduction to C	Lecture (2 hr)
Week 02	Addressable memory 1, string and arrays	Lecture (2 hr)
Week 02	First C programs with text processing	Tutorial (2 hr)
Week 03	Addressable memory 2, structures and files	Lecture (2 hr)
Week 03	C pointer basics, C library functions	Tutorial (2 hr)
Week 04	Memory management and linked lists	Lecture (2 hr)
Week 04	C pointers, structs, unions and files	Tutorial (2 hr)
Week 05	C compiler stages and function pointers, Unit testing	Lecture (2 hr)
Week 05	Dynamic memory and debugging	Tutorial (2 hr)
Week 06	Debugging C, processes and bit fields	Lecture (2 hr)
Week 06	Program structure, common C errors	Tutorial (2 hr)
Week 07	Parallelism and concurrency	Lecture (2 hr)
Week 07	Compiler stages and linked lists	Tutorial (2 hr)
Week 08	1. Signals and IPC; 2. Thread synchronisation, POSIX threads	Lecture (2 hr)
Week 09	Thread safety: Testing and debugging	Lecture (2 hr)
Week 09	Parallelism and concurrency	Tutorial (2 hr)
Week 10	Scalable algorithm templates	Lecture (2 hr)
Week 10	Shared memory	Tutorial (2 hr)
Week 11	Performance - memory and measure	Lecture (2 hr)
Week 11	Thread constructs and reliability	Tutorial (2 hr)
Week 12	Revision and examination overview	Lecture (2 hr)
Week 12	Revision	Tutorial (2 hr)

Attendance and class requirements

Course websites:

The course website on edstem.org will contain information, including important announcements. Teaching staff will be communicating to all students and it is considered part of the course. Students are expected to regularly visit this website to know these announcements and information concerning format and schedule of assessment. Canvas is a website that will be used to disseminate the online lecture recordings and for publishing of results.

Online attendance:

Students are asked to attend their tutorial class each week as part of their assessment. Students are advised to follow the procedures concerning late attendance, or failure to attend. Such procedures will be presented in the course lectures.

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 on the Library eReserve link available on Canvas.

Computer Systems: A Programmer’s Perspective, Randal E. Bryant and David R. O`Hallaron, 9781292101767, 3rd edition, Pearson Education, 2016, Boston

Reference books

Brian W. Kernighan and Dennis M. Ritchie – The C Programming Language. Prentice Hall. 1988. 0-13-110362-8
Lin and Snyder. Principles of Parallel Programming. Pearson Education. 2008
Jeri R. Hanly, Elliot B. Koffman. Problem Solving and Program Design in C. 6th Edition. Addison Wesley. 2010. ISBN:0321198034. Note: 4th edition does not contain the chapter on IPC
Paul Davies. The Indispensable Guide to C. 1st Edition. 1995. ISBN-13: 978-0201624380

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. apply code quality strategies appropriate for C, including preprocessor techniques, and use of common idioms
LO2. use Unix commands and system calls (including usage of flags etc) from online manual system
LO3. demonstrate the approach and concepts of Unix, including its tools philosophy, processes (including pipes and redirection), the file system, and the shell
LO4. compose correct, clean code in C that allocates, deallocates and manages memory
LO5. construct correctly implement standard linked list data structures. Higher performance could involve slightly more complicated structures such as binary search trees
LO6. assess code execution using debugging tools
LO7. apply a thorough automated testing regime using tools such as make, diff, scripts to present the outcomes, and a tool to manage regression testing. Higher performance could involve ability to construct such a regime
LO8. read and write code that correctly uses the main standard library functions, especially for I/O, file handling, and string handling. Higher performance could involve elegant use of these functions, particularly avoiding idioms which are extremely inefficient.
LO9. evaluate common memory-related errors (such as memory leaks, dangling pointers) and how to avoid these. Higher performance could involve detecting errors in example code, and fixing them using debuggers
LO10. construct, debug, and evaluate parallel or concurrent programs.

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.

Further emphasis on linking and build systems

Additional information

Every week students must:

Read the required sections of literature
Attend and take notes for the Lecture (Mondays)
Make progress on and complete the Task sets (as required)
Make progress on and complete the Assignments (as required)
Prepare for the Lab by reviewing reading, lecture and lab questions
Attend and participate in weekly Lab with tutor(as timetabled)

Additionally:

Students should ask questions on edstem.org
Students are encouraged to attend and/or watch the OPTIONAL seminar (Wednesday evening)

Access to online assessments. Access to course contents: Lecture, Laboratory, online lessons, challenges etc. Access to important announcements, discussion and support forum.

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

Attendance and class requirements

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

On this page

Useful links

Media

Student links

About us

Connect

Current students

COMP2017: Systems Programming

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

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

Attendance and class requirements

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

On this page

Useful links

Media

Student links

About us

Connect