Unit Outline
KIT205
Data Structures and Algorithms
Semester 1, 2024
Robert Ollington
School of Information and Communication Technology
College of Sciences and Engineering
CRICOS Provider Code: 00586B

Unit Coordinator
Robert Ollington
Email: Robert.Ollington@utas.edu.au
 

What is the Unit About?
Unit Description
This unit extends the first year treatment in KIT107 of standard data structures and algorithms for solving computational problems. Topics include: data structures (such as balanced trees and hash tables) for collections, (binary heaps for) priority queues, sorting algorithms (e.g. heapsort, mergesort and quicksort), graphs and graph algorithms (e.g. for searching, topological sorting, critical path analysis, shortest paths, minimum spanning trees, network flow), pattern finding (for substrings and regular expressions), algorithmic problem solving and algorithm design techniques (e.g. greed, divide and conquer, dynamic programming, backtracking).
Intended Learning Outcomes
As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.
On completion of this unit, you will be able to:
1.
transform a real-world problem into a simple abstract form that is suitable for efficient computation
2.
implement common data structures and algorithms using a common programming language
3.
analyse the theoretical and practical run time and space complexity of computer code in order to select algorithms for specific tasks
4.
apply common algorithm design strategies to develop new algorithms when there are no pre-existing solutions
Requisites
REQUISITE TYPE
REQUISITES
Pre-requisite
KIT107
Alterations as a result of student feedback
Increased clarity around testing requirements for assignments.  Added more examples to tutorial materials.  Formalised in-tutorial presentation of weekly materials.
 
 

Teaching arrangements
ATTENDANCE MODE
TEACHING TYPE
LEARNING ACTIVITY
CONTACT HOURS
FREQUENCY
On Campus
Independent Learning
Involving reading, listening to audio, watching video, and/or completing exercises and/or quizzes, self-study is individual work undertaken when the student chooses (i.e. asynchronous), most likely through engagement with MyLO. The content is examinable, and may need to be completed prior to attending classes and/or attempting assessment tasks.
2
Weekly
Tutorial
A structured real-time (i.e. synchronous) activity in a small-group setting where the primary purpose is the clarification, exploration or reinforcement of subject content presented or accessed at another time or place (e.g. lecture, preparatory work). It is reliant on student-teacher and student-student interaction and dialogue for achievement of its learning outcomes. The students enrolled in the tutorial are expected to attend.
2
Weekly
Attendance / engagement expectations
If your unit is offered On campus, it is expected that you will attend all on-campus and onsite learning activities. This is to support your own learning and the development of a learning community within the unit. If you are unable to attend regularly, please discuss the situation with your course coordinator and/or our UConnect support team.

If your unit is offered Online, it is expected you will engage in all those activities as indicated in the Unit Outline, including any self-directed learning.

If you miss a learning activity for a legitimate reason (e.g., illness, carer responsibilities) teaching staff will attempt to provide alternative activities (e.g., make up readings) where it is possible.
 
 
 
 

How will I be Assessed?
 
For more detailed assessment information please see MyLO.
Assessment schedule
ASSESSMENT TASK #
ASSESSMENT TASK NAME
DATE DUE
WEIGHT
LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:
Assignment - Data Storage Application
Week 8
20 %
LO1, LO2, LO3
Assessment Task 2:
Assignment - Graph-based Computing Problem
Week 14
40 %
LO1, LO2, LO3, LO4
Assessment Task 3:
Quizzes (x10)
Refer to Assessment Description
20 %
LO2, LO3, LO4
Assessment Task 4:
Lab Work
Refer to Assessment Description
20 %
LO2
 
Assessment details
    
Assessment Task 1: Assignment - Data Storage Application
Task Description:
Implement data storage application using linked list and binary search tree data structures and associated algorithms.

Task Length:
~500LOC
Due Date:
Week 8
Weight:
20 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Adapt generic data structures for use in a specific problem
LO1
2
Implement generic list data structures and algorithms
LO2
3
Implement generic tree data structures and algorithms
LO2
4
Evaluate performance of alternative data structures
LO3
 
Assessment Task 2: Assignment - Graph-based Computing Problem
Task Description:
Use graph data structures and algorithms to solve a graph-based computing problem.

Task Length:
~500LOC 500 words
Due Date:
Week 14
 

Weight:
40 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Apply graph data structures and algorithms to solve a specific problem
LO1
2
Implement generic graph data structures and algorithms
LO2
3
Develop and analyse algorithms to solve a real world problem
LO1, LO3, LO4
 
Assessment Task 3: Quizzes (x10)
Task Description:
Use written and diagrammatic approaches to answer questions related to data structures and algorithms.Due Monday 9am of weeks 4-12

Task Length:
10 x 30mins
Due Date:
Refer to Assessment Description
Weight:
20 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Analyse short code segments to determine run time and space complexity
LO3
2
Justify algorithm choice based on run time and space complexity
LO3
3
Identify the design strategies used by common algorithms
LO4
4
Apply one or more design strategies to the development of a new algorithm
LO4
5
Apply algorithms related to common data structures
LO2
 
Assessment Task 4: Lab Work
Task Description:
Demonstrate completion of lab work covering implementation of foundation data structures and test code. Assessed in week 5 (lists and search trees) and week 9 (graphs).

Task Length:
100LOC
Due Date:
Refer to Assessment Description
Weight:
20 %
 
CRITERION #
CRITERION
MEASURES INTENDED
LEARNING OUTCOME(S)
1
Implement and test a linked list data structure
LO2
2
Implement and test a search tree
LO2
3
Implement and test a graph data structure
LO2
 
 
 

How your final result is determined
To pass this unit, you need to demonstrate your attainment of each of the Intended Learning Outcomes, achieve a final unit grade of 50% or greater, and pass any hurdle tasks.
 
Submission of assignments
Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.
 
Requests for extensions
If you are unable to submit an assessment task by the due date, you should apply for an extension.
 
A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.
 
The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.
Late penalties
Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.
 
Review of results and appeals
You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.
 
 
 

Required Resources
Required reading materials
N/A
 
Recommended reading materials
N/A
 
Other required resources
COMPUTING FACILITIES
The Discipline of ICT has PC labs, Mac labs, and special purpose Networking labs at the Newnham and Sandy Bay campuses. All students are provided with logins for Windows, Macintosh and Unix environments. If you have not used these facilities before please contact the ICT Help Desk. If you would like to access these facilities after hours please contact the ICT Help Desk.

USE OF FACILITIES
Use of computing facilities provided by the Discipline of ICT is subject to the Discipline's Ethics Guidelines, details of which are posted at http://www.utas.edu.au/technologyenvironmentsdesign/ict/currentstudentresources/ethicsguidelines.

Copies of the guidelines are also available in all ICT labs. The Discipline's facilities may only be used for study related purposes, and may not be used for personal gain. Antisocial behaviour in labs such as game playing, viewing pornography, loud discussion, audio without the use of headphones, etc is strictly prohibited in all labs at all times.

Eating, drinking, and smoking is not permitted in the labs. Before being granted access to the Discipline's facilities, you will be required to sign a declaration that you have read and understand these guidelines, and that you will abide by them. You will also be required to complete the relevant MyLO course to gain access. Disciplinary action may be taken against students who violate the guidelines. Details about gaining access to the labs can be found at ICT Reception.