COMP SCI 2103 - Algorithm Design & Data Structures

North Terrace Campus - Semester 2 - 2024

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: review of class hierarchies, inheritance, friends, polymorphism and type systems; recursion; OO design principles, abstract data types, testing and software reuse; introductory data structures: linked lists, stacks, queues, trees, heaps, algorithmic strategies for searching and sorting data in these structures; introductory complexity analysis.

  • General Course Information
    Course Details
    Course Code COMP SCI 2103
    Course Algorithm Design & Data Structures
    Coordinating Unit Computer Science
    Term Semester 2
    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
    Incompatible COMP SCI 1103, COMP SCI 2202, COMP SCI 2202B
    Restrictions Not available to B. Information Technology students
    Assessment Written exam and/or assignments
    Course Staff

    Course Coordinator: Dr Anna Kalenkova

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On 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)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.


    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.


    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.


    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.


    Attribute 5: Intercultural and ethical competency

    Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.


    Attribute 7: Digital capabilities

    Graduates are well prepared for living, learning and working in a digital society.


    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

  • Learning Resources
    Required Resources
    The 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.**

    * Limited simultaneous online copies available through MyUni course readings
    ** Unlimited simultaneous online copies available through MyUni course readings

    Personal copies can be purchased. Limited physical copies are available from the library in the short term loan collection.
    Recommended Resources
    Students who have not studied C++ as a programming language and are entering this course are strongly advised to undertake self study in C++ before underaking this course.
    Online Learning
    In this course, we use the myUni online Learning Management System. The link for the course is at
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course has three contact activities: lectures, workshops and practicals. Each of these activities will provide you with the resources necessary to understand the course material.

    Lectures are split between
    1) key concept videos which are pre-recorded and present information, and
    2) in class lecture sessions where we will work on problems together and discuss concepts in more detail.  These in-class sessions will be recorded for review purposes, but the in-class sessions are not designed for passive viewing and will contain periods where students are working on problems in class for which the recording will only have background noise.

    Practicals are an in-lab activity session where you will work on the weekly programming tasks involving algorithms and data structures that you are learning using  C++.  Practical supervisors are stationed around the lab area to assist you or give you feedback. 

    Workshops focus on discussions around design choices and analysis of performance with different data sets.

    All activities prepare you for practical exams and final exam and we expect you to engage with and contribute to all scheduled sessions.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Students are expected to spend 10-12 hours per week on this course.
    There will be 4-5 hours contact time for learning and teaching activities each week and students will be working in groups and individually an additional 6-8 hours per week on average to carry out the required learning and teaching activities for acquiring the expected knowledge, understanding, and skills in this course.
    Learning Activities Summary
    The weekly pattern is three one-hour lectures and a two-hour practical session, with a tutorial every fortnight. The outline course content is:

    Week 1
    Review of fundamental C++ programming techniques, Object Oriented Design Principles

    Week 2
    Abstract Data Types

    Week 3

    Week 4
    Analysing algorithm performance

    Week 5
    Computational complexity 

    Week 6
    Searching & Sorting Algorithms

    Week 7
    List structures - Linked lists

    Week 8
    Stack and Queue ADTs

    Week 9
    Tree ADTs

    Week 10
    Heap ADTs

    Week 11
    Selecting ADTs and Algorithmic Strategies

    Week 12
    Finishing off, Summary & Exam prep
    Specific Course Requirements
    There are no specific course requirements.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    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 20 Individual Summative Week 4,8 1. 4. 10.
    Practical Assignments 24  Individual Summative Weeks 1-12 1. 2. 3. 4. 5. 6. 7. 9. 10.
    Workshop - active participation 3 Individual Summative Weeks 1-12 1. 2. 3. 4. 5. 6. 7. 9. 10.
    Quizzes 3 Individual Summative Weeks 1-12
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
    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.

    Assessment Related Requirements
    Students must achieve an overall passing mark and at least 40% in the main exam.

    All assessment items must be submitted by specified due dates.  All extensions requests must comply with the Modified Arrangements for Coursework Assessment Policy
    Assessment Detail
    Workshop participation requires you to work in groups to generate solutions to problems and present your groups' work.

    Practical assignments are programming assignments related to the course topics which can be done in groups or individually.

    Practical examinations are lab based programming and theory exams held during scheduled practical time. They assess content covered in the weeks before they are held.

    Written examination is a 2-hour theory and programming structure examination with questions from across the course content.

    Submission details for all activities are available in MyUni but the majority of your submissions will be online and may be subjected to originality testing through Turnitin or other mechanisms. You will receive clear and timely notice of all submission details in advance of the submission date.

    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 Access Adelaide.

  • 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 ( 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.

  • Student Support
  • Policies & Guidelines
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    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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