COMP SCI 2103 - Algorithm Design & Data Structures
North Terrace Campus - Semester 1 - 2021
General Course Information
Course Code COMP SCI 2103 Course Algorithm Design & Data Structures Coordinating Unit School of Computer Science Term Semester 1 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 Cheryl Pope
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 two contact activities: lectures 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.Â
Practicals are an in-lab activity session where you will work on the weekly programming tasks in C++, while receiving feedback from practical supervisors who are stationed around the lab area. You will need to discuss your work with the supervisors and other students to ensure that you have understood everything. Carrying out the practical tasks is very important to be able to successfully complete the practical examinations.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
You are expected to allocate 5 hours per week for conatact time, prep and review and approximately 5 hours per week for practicals (as a minimum). On average, you should require no more than 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 outline course content is:
Review of fundamental C/C++ programming techniques, pointer arithmetic and function pointers, memory errors and core dumps
Abstract data types and class hierarchies
Inheritance, friends, and overloading
Using classes, OO Design principles, testing and design
Principles of software re-use and maintenance, recursion
Ethics, polymorphism, using ADTs to produce usable structures
Introduction to complexity analysis, upper and lower complexity bounds, best-case and worst-case, big O, little o, omega and theta
Complexity analysis, searching and sorting Algorithms
Recursive complexityâÂ¨, linked lists and stacks
Queues, other linked list based data structures
Trees, algorithmic strategies
Problem solving, programming paradigms, introduction to type systems
The course is structured to take you from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design.
The summary of the areas covered in this course are:
Review and development of previous knowledge of C++
Fundamental data structures
Fundamental Computing Algorithms
Basic Algorithmic Analysis
Overview of programming languages
Professional Skills Development
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 Examination 50 Individual Summative Exam Period Min 40% 1. 2. 3. 4. 5. 6. 8. 10. Practical Examinations 40 Individual Summative Week 3,6 1. 4. 10. Practical Assignments 5 Group Formative Weeks 2-12 1. 2. 3. 4. 5. 6. 7. 9. 10. Workshop - active participation 5 Group 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.
Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.
Practical examinations and final examinations will be online.
Assessment Related RequirementsStudents must achieve an overall passing mark and least 40% in the main exam.
SubmissionAssignments must be submitted through electronic means that will be clearly identified on the assignment rubric.
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.
Any other work submitted will be marked and 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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