COMP SCI 2103 - Algorithm Design & Data Structures
North Terrace Campus - Semester 2 - 2021
General Course Information
Course Code COMP SCI 2103 Course Algorithm Design & Data Structures Coordinating Unit Computer Science Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 6 hours per week Available for Study Abroad and Exchange Y Prerequisites COMP SCI 1102 or COMP SCI 1202 Incompatible COMP SCI 1103, COMP SCI 1203, COMP SCI 2004, COMP SCI 2202, COMP SCI 2202B Course Description The course is structured to take students from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design. Topics include: abstract data types, class hierarchies, inheritance, friends, polymorphism and type systems; OO design principles, testing and software reuse; algorithmic strategies and introductory complexity analysis; recursion, linked lists, stacks, queues and trees.
Course Coordinator: Dr Chitchanok Chuengsatiansup
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Program C++ in the OO paradigm, 2 Explain fundamental computing algorithms, 3 Analyse algorithms and identify key algorithmic strategies, 4 Demonstrate familiarity with fundamental software engineering practices, 5 Demonstrate knowledge of programming language design issues, 6 Work competently in a group to learn software concepts. 7 Use abstract data types to help solve programming problems
The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
The course is designed to develop the following Elements of Competency: 1.1 1.2 1.3 1.4 1.5 1.6 2.1 2.2 3.1 3.2 3.6
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1-7 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
3,7 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
6 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1,2,4,5 Intercultural and ethical competency
- adept at operating in other cultures
- comfortable with different nationalities and social contexts
- able to determine and contribute to desirable social outcomes
- demonstrated by study abroad or with an understanding of indigenous knowledges
6 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
Required ResourcesThe reference text for this course are:
- Problem Solving with C++, Walter Savitch.
- Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.
- Algorithms and Data Structures: The Basic Toolbox, Kurt Mehlhorn and Peter Sanders.
Recommended ResourcesStudents who have Java as a programming language and are entering this course are strongly encouraged to make use of the simple on-line resource that is available in the course MyUni modules.
Online LearningIn this course, we use the myUni online Learning Management System. The link for the course is at https://myuni-canvas.adelaide.edu.au/
Learning & Teaching Activities
Learning & Teaching ModesThe course has three contact activities: lectures, tutorials and practicals. Each of these activities will provide you with the resources necessary to understand the course material.
Lectures will present information and provide an opportunity for the introduction and discussion of programming, algorithmic and other material. You should expect to attend all of these and participate in small group work.
Workshops will provide a small group discussion forum where you and your peers will practice applying knowledge to problem solving. The goal of workshops is to give you necessary practice in formulating answers to key questions.
Practicals are an in-lab activity session where you will work on the weekly course assignments in C++, while receiving feedback from practical markers who are stationed around the lab area. You will need to explain your work to the marker to ensure that you have understood everything that we're trying to pass on.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.You are expected to allocate 4-5 hours per week for lectures (including reading/reviewing) approximately 4-5 hours per week for practicals (as a minimum) and 2 hours per fortnight for workshops. On average, you should expect to dedicate 10-12 hours per week for this course.
Learning Activities SummaryThe weekly pattern is three one-hour lectures and a two-hour practical session, with a tutorial every fortnight. The lecture topics and assignment descriptions, including a schedule, are all available on the course website.
Specific Course RequirementsThere are no specific course requirements.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Task Weighting (%) Individual/ Group Formative/ Summative Due (week)* Hurdle criteria Learning outcomes Written or Oral Examination 50 Individual Summative Week 13 Min 40% 1. 2. 3. 4. 5. 6. 8. 10. Practical Examinations 40 Individual Summative Week 4,8 1. 4. 10. Practical Assignments 10 Individual Formative Weeks 2-12 1. 2. 3. 4. 5. 6. 7. 9. 10. Total 100
This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s):
This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.
**CBOK is the Core Body of Knowledge for ICT Professionals defined by the Australian Computer Society. The alignment in the table above corresponds with the following CBOK Areas:
1. Problem Solving
2. Professional Knowledge
2.2 Professional expectations
2.3 Teamwork concepts & issues
2.4 Interpersonal communications
2.5 Societal issues
2.6 Understanding of ICT profession
3. Technology resources
3.1 Hardware & Software
3.2 Data & information
4. Technology Building
4.2 Human factors
4.3 Systems development
4.4 Systems acquisition
5. ICT Management
5.1 IT governance & organisational
5.2 IT project management
5.3 Service management
5.4 Security management
Assessment Related RequirementsHurdle Requirement: If your overall mark for the course is greater than 44 F but, your mark for the final written exam is less than 40%, your overall mark for the course will be reduced to 44 F.
No information currently available.
All programming submissions will be made through Gradescope (https://www.gradescope.com). Other assignments may be submitted through other electronic means that will be clearly identified on the assignment rubric.
Both electronic systems provide cover sheets for submitted work. No physical submissions of work will be accepted unless specifically requested by the lecturer.
The School of Computer Science observes a strict lateness policy. the mark for late submissions will be capped, based on how many days late it is:
1 day late – mark capped at 75%
2 days late – mark capped at 50%
3 days late – mark capped at 25%
more than 3 days late – no marks available.
Extensions may be requested in advance for medical or compassionate reasons but (1) all requests must be accompanied by documentation, (2) extensions awarded will be in proportion to the time lost that is supported by documentation, (3) extensions are almost never granted on the final day unless the issue is both severe and unforeseen, and (4) extensions are never granted because you have been busy, have managed your time poorly or are overloaded in other courses.
Programming marks will be returned to you within 10 working days. If your work is considered to not be a sufficient attempt, you may be asked to resubmit the work. If we can identify that you are trending towards overall insufficient progress (and at risk of triggering the minimum performance threshold) then we may contact you to make you explicitly aware of this risk, however, you should be tracking your own progress and making your best attempt at every piece of work, rather than aiming to scrape by.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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