COMP SCI 2201NA - Algorithm & Data Structure Analysis
Ngee Ann Academy - Trimester 3 - 2014
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General Course Information
Course Details
Course Code COMP SCI 2201NA Course Algorithm & Data Structure Analysis Coordinating Unit Computer Science Term Trimester 3 Level Undergraduate Location/s Ngee Ann Academy Units 3 Prerequisites One of COMP SCI 1009, COMP SCI 1007, COMP SCI 1103, COMP SCI 1203, or COMP SCI 2202 Incompatible COMP SCI 2004 Course Staff
Course Coordinator: Dr Bradley Alexander
Lecturer: Dr Lye Kong Wei
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
1. 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 -
Learning Resources
Required Resources
Textbook
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 Resources
Recommended 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 Learning
Course Website: -
Learning & Teaching Activities
Learning & Teaching Modes
Lectures and Tutorials. Most tutorials will be handed in for assessment.Workload
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 Summary
The following details the topics to be introduced by the lectures.
The tutorial topics will broadly follow this schedule
- Introduction
- Integer-Arithmetics
- Recursive-Multiplication
- Karatsuba-Multiplication
- Binary-Search-Trees
- Binary-Search-Invariants
- Priority-Queues
- PQ-HeapSort-Binary-Search-Trees
- BST-average-case
- AVL-Trees
- Skip-Lists
- Hashing1
- Hashing2
- Graphs
- Graph-Representations-BFS
- DFS-Connected-Components
- Shortest-Paths1
- Shortest-Paths2
- DynamicProgramming
- Minimum-Spanning-Trees
- Minimum-Spanning-Trees2
- P-and-NP
- P-and-NP2
- Exam-Preparation
Specific Course Requirements
There are no specific requirements for this course beyond prerequisite knowledge and the ability to attend the lectures and tutorials. -
Assessment
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 Summary
The 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 of up to two people) 30% of the marks for the course.Assessment Related Requirements
A minimum score of 40% is required in each 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 required 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 Detail
The 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.Submission
Details 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.Course Grading
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 .
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Student Feedback
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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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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Fraud Awareness
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鈥檚 disciplinary procedures.
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