COMP SCI 7201 - Algorithm & Data Structure Analysis
North Terrace Campus - Semester 2 - 2015
General Course Information
Course Code COMP SCI 7201 Course Algorithm & Data Structure Analysis Coordinating Unit School of Computer Science Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Prerequisites COMP SCI 7080 or COMP SCI 7202 Incompatible COMP SCI 7082 Assumed Knowledge COMP SCI 7202 Course Description Program development techniques including basic ideas of correctness and proof; Notions of complexity and analysis; Recursion. Approaches to Problem Solving. Notion of abstract data type, representation of lists, stacks, queues, sets, trees and hash tables. Graphs and Graph Traversal
Course Coordinator: Dr Mingyu Guo
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning Outcomes1. Skills in performing analysis of given recursive and iterative algorithms.
2. Understanding and performing simple proofs of algorithmic complexity and correctness.
3. An ability to understand and derive recurrences describing algorithms and properties of data structures.
4. An understanding of the implementation and efficiency of a range of data structures including, trees, binary heaps, hash-tables and graphs.
5. An understanding of a variety of well-known algorithms on some of the data structures presented.
6. The ability to implement and use these algorithms in code.
7. A foundational understanding of intractability. An understanding of proof techniques for NP- Completeness.
8. An ability to solve new analytic and algorithmic problems.
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) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1-8 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1,8 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 1,3,6,7,8 A proficiency in the appropriate use of contemporary technologies. 2,6,7 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 1,8 A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 1,2,7,8
The textbook for this course is Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, Third Edition, MIT Press.
Recommended ResourcesRecommended further reading:
Algorithms and Data Structures - The Basic Toolbox by Kurt Mehlhorn and Peter Sanders, Springer, 2008.(the full text is available on the Author’s website).
Learning & Teaching Activities
Learning & Teaching ModesLectures and Tutorials. Most tutorials will be handed in for assessment.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.The workload is approximately 12 hours per week during semester time. This consists of an average of 2.5 hours of contact time and the remaining time for study and working on tutorial submissions.
Learning Activities SummaryThe following details the topics to be introduced by the lectures
The tutorial topics will broadly follow this schedule
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 SummaryThe course assessment consists of two components:
• A written exam worth 70% of the marks for the course
• Written submissions to tutorials (some, optionally, done in teams) 30% of the marks for the course.
Below are the CBOK mappings:
Component Abstraction Design Interpersonal Communication Programming
Lecture x x x
Tutorials 3 5 3 5
Exam 3 4 3
Details of the Australian Computer Society's Core Bode of Knowledge (CBOK) can be found in
Below are the mappings to learning outcomes and graduate attributes:
Component Weight Learning Outcomes Graduate Attributes
Tutorials 30% 1,3,4,5,6,8 1,2,3,4,5,6
Exam 70% 1,2,3,4,5,6,7,8 1,2,3,4,5
Assessment Related RequirementsYou are also encouraged to attend all the tutorial sessions. Application for exemptions based on medical and/or compassionate grounds must be made to the course coordinator.
Assessment DetailThe written exam will be centrally administered by examinations and held at the end of semester.
Each tutorial will be based on materials presented at that stage of the course or on readings drawn from reference materials.
Three out of the six tutorials will be assessed with each tutorial being worth 5-10% of the course mark. Some tutorials will be based on group work.
Tutorials will be marked within one and a half weeks of the tutorial submission deadline. Brief written feedback will be provided along with marks.
SubmissionDetails of the submission of tutorials will be written on each tutorial handout. The submission time for tutorials will usually be only one day prior to the first tutorial presentation. As such no late submission is accepted unless prior arrangement is made with the course coordinator for an extension on medical or compassionate grounds.
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.
- Academic Support with Maths
- Academic Support with writing and speaking skills
- Student Life Counselling Support - Personal counselling for issues affecting study
- International Student Support
- AUU Student Care - Advocacy, confidential counselling, welfare support and advice
- Students with a Disability - Alternative academic arrangements
- Reasonable Adjustments to Teaching & Assessment for Students with a Disability Policy
- LinkedIn Learning
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangement Policy
- Academic Honesty Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Elder Conservatorium of Music Noise Management Plan
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.
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