COMP SCI 2201NA - Algorithm & Data Structure Analysis
Ngee Ann Academy - Trimester 3 - 2016
General Course Information
Course Code COMP SCI 2201NA Course Algorithm & Data Structure Analysis Coordinating Unit School of Computer Science Term Trimester 3 Level Undergraduate Location/s Ngee Ann Academy Units 3 Available for Study Abroad and Exchange N Prerequisites One of COMP SCI 1009, COMP SCI 1007, COMP SCI 1103, COMP SCI 1203, or COMP SCI 2202 Incompatible COMP SCI 2004 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 Bradley AlexanderLecturer: Dr Poh Kok Loo
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) 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)
1-8 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
1,2,8 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
1-8 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1,6,8 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
8 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
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).
Online LearningCourse Website: https://forums.cs.adelaide.edu.au/forums/course/view.php?id=1031
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 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
Specific Course RequirementsThere are no specific requirements for this course beyond prerequisite knowledge and the ability to attend the lectures and tutorials.
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 Related RequirementsA minimum score of 40% is required in the tutorial component of the course. Failure to achieve this score will result your course mark being capped at 44F with opportunity for additional assessment being awarded at the discretion of the school.
You are also expected to attend a minimum of five out of six 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.
Five out of the six tutorials will be assessed with each tutorial being worth 6% of the course mark. Where it is written on the tutorial, students will be allowed to work on the questions in teams of up to two people.
Tutorials will be marked within one and a half weeks of the tutorial submission deadline. Brief written feedback will be provided along with marks.
Below are the CBOK mappings for course assessments
Component Weighting CBOK Areas Final written exam 70% 1,2,8 Assignments 30% 1,2,4,7,8,9,11
Details of the Australian Computer Society's Core Bode of Knowledge (CBOK) can be found in this document.
Below are the mappings to learning outcomes and graduate attributes:
Component Weight Learning Outcomes Graduate Attributes Final written exam 70% 1,2,3,4,5,6,7,8 1,2,3,4,5 Assignments 30% 1,3,4,5,6,8 1,2,3,4,5,6
SubmissionDetails of the submission of tutorials will be written on each tutorial handout. The submission time for tutorials will usually be only one to two days prior to the first tutorial presentation. As such it will only be possible to accept tutorial submissions up to one day late (capped at a maximum of 75% for lateness) unless prior arrangement is made with the course coordinator for an extension on medical or compassionate grounds. In all cases where the submission is late the submission may have to be made direct to the lecturer.
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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- International Student Support
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- Reasonable Adjustments to Teaching & Assessment for Students with a Disability Policy
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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
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