COMP SCI 2103 - Algorithm Design & Data Structures

North Terrace Campus - Semester 1 - 2022

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: abstract data types, class hierarchies, inheritance, friends, polymorphism and type systems; OO design principles, testing and software reuse; algorithmic strategies and introductory complexity analysis; recursion, linked lists, stacks, queues and trees.

  • General Course Information
    Course Details
    Course Code COMP SCI 2103
    Course Algorithm Design & Data Structures
    Coordinating Unit School of Computer Science
    Term Semester 1
    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 or COMP SCI 1202
    Incompatible COMP SCI 1103, COMP SCI 1203, COMP SCI 2004, COMP SCI 2202, COMP SCI 2202B
    Restrictions Not available to B. Information Technology students
    Course Description 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: abstract data types, class hierarchies, inheritance, friends, polymorphism and type systems; OO design principles, testing and software reuse; algorithmic strategies and introductory complexity analysis; recursion, linked lists, stacks, queues and trees.
    Course Staff

    Course Coordinator: Dr Cheryl Pope

    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.

    1-7

    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.

    3,7

    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.

    6

    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.

    1,2,4,5

    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.

    6

    Attribute 7: Digital capabilities

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

    4

    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.

    1,3,5,7
  • 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.
    Personal copies can be purchased. Limited copies are available from the library in the short term loan collection and online.
    Recommended Resources
    Students who have Java as a programming language and are entering this course are strongly encouraged to make use of the simple on-line resource that is available in the course MyUni modules.
    Online Learning
    In this course, we use the myUni online Learning Management System. The link for the course is at https://myuni-canvas.adelaide.edu.au/
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course has two contact activities: lectures and practicals. Each of these activities will provide you with the resources necessary to understand the course material.

    Lectures will present information and provide an opportunity for the introduction and discussion of programming, algorithmic and other material. You should expect to attend all of these and participate in small group work. 

    Practicals are an in-lab activity session where you will work on the weekly programming tasks in C++, while receiving feedback from practical supervisors who are stationed around the lab area. You will need to discuss your work with the supervisors and other students to ensure that you have understood everything. Carrying out the practical tasks is very important to be able to successfully complete the practical examinations.
    Workload

    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 3-4 hours contact time for learning and teaching activities and students will be working in groups and individually 8-9 hours 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, Abstract data types

    Week 2
    Class hierarchies

    Week 3
    Inheritance, polymorphism, friends, and overloading

    Week 4
    Recursion

    Week 5
    Introduction to complexity analysis

    Week 6
    Searching Algorithms

    Week 7
    Sorting Algorithms

    Week 8
    Linked lists and stacks

    Week 9
    Queues, other linked list based data structures

    Week 10
    Heaps

    Week 11
    Trees

    Week 12
    Problem solving, algorithmic strategies

    The course is structured to take you from an introductory knowledge of C++ to a higher level, as well as addressing some key areas of computer programming and algorithm design.

    The summary of the areas covered in this course are:

    Review and development of previous knowledge of C++
    Fundamental data structures
    Object-oriented Programming
    Fundamental Computing Algorithms
    Recursion
    Basic Algorithmic Analysis
    Algorithmic Strategies
    Overview of programming languages
    Software Engineering
    Software Evolution
    Professional Skills Development
    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  25 Group or Individual Formative Weeks 2-12 1. 2. 3. 4. 5. 6. 7. 9. 10.
    Workshop - active participation 5 Group Formative Weeks 2-12 1. 2. 3. 4. 5. 6. 7. 9. 10.
    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 least 40% in the main exam. 


    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
    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 (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.

  • Student Support
  • Policies & Guidelines
  • 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’s disciplinary procedures.

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