COMP SCI 2203 - Problem Solving & Software Development

North Terrace Campus - Semester 2 - 2024

This course presents students with open-ended and complex programming problems that focus on developing their software design and implementation skills. The course will also introduce software engineering principles, and particularly approaches to software quality.

  • General Course Information
    Course Details
    Course Code COMP SCI 2203
    Course Problem Solving & Software Development
    Coordinating Unit Computer Science
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites One of COMP SCI 1103, COMP SCI 1203, COMP SCI 2103, COMP SCI 2202, COMP SCI 2009 or COMP SCI 2202B
    Assessment Assignments, practicals and practical exams
    Course Staff

    Course Coordinator: Dr Cruz Izu

    Cruz Izu (
           refer to myuni  

    Course Timetable

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

    Contact hours for this course consist of a two hour lecture on Tuesday and a two hour laboratory session on Wednesday.

    Practical sessions will be devoted to programming practice and practical exams.
    Lectures will mix presentation of concepts with programming and problem-solving exercises.
  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

    1 Recognise the broad algorithmic category to which a problem belongs, e.g. brute-force, recursive, dynamic programming, divide-and-conquer
    2 Formulate a short solution sketch to a programming problem
    3 Demonstrate the ability to quickly assess the efficiency of a proposed solution with respect to expected input data
    4 Build your own process of design, testing, experimentation and programming
    5 Apply your own process to the timely production of solutions to a range of programming problems
    6 Complete practice examples with reasonable frequency in a timely manner
    7 Demonstrate the ability to reflect in detail on your own programming performance and software development processes in a frequent, timely and useful manner
    8 Designing and/or selecting new practice exercises in to address gaps in performance highlighted by your reflections

    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: 1.2   1.3   1.5   1.6   2.1   2.2   2.3   2.4   3.3   3.4   3.5   

    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 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 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
    There is no textbook for this course. Many of the learning resources will be provided online at the course website

    The learning is based on deliberate practice by solving multiple excercise each week selected from a set published weekly in myUni.
    Reflection on process, outcomes and skill gaps is a core element of deliberate practice.  Reflection during problem solving, code design and implementation for each exercise should be captured in a logbook. 

    Recommended Resources
    In addition to the resources above the following are likely to prove very useful:

    The topcoder algorithms competition website: including the algorithms tutorials: 

    We also recommend the following reference: "The Algorithm Design Manual", Steven S. Skeina, Second Edition, Springer. This book is a great (and very readable) reference summarising a broad range of common algorithms as well as decscribing common algorithmic categories and approaches to solving computational problems.

    Additional links for program development and practice techniques will be added to course website before and during the semester.
    Online Learning
    The course forums (and other online resources) can be accessed in the subject  webpage at Canvas. 

  • Learning & Teaching Activities
    Learning & Teaching Modes
    Lectures, Lecture Exercises, Out-of-class practice, Laboratory sessions, Practical Exams.

    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 4 hours of contact time and the remainder is for out of class practice and working on assignments.
    Learning Activities Summary
    Learning activities will consist of:

    • In-lecture exericess done alone and in groups -  solving algorithmic problems - reflecting and improving on problem solving processes.
    • Laboratory sessions solving algorthmic practice exercises - applying newly learned techniques - focusing on gaps in skills.
    • Practical Exams - solving algorithmic problems in a timely manner
    • Out-of-class weekly practice including reflection and design
    These activities will be graduated in difficultly and challenge as the semester progresses. 

    We will also examine a range of broad algorithmic categories including some or all of:
            brute force, recursion, dynamic programming, divide and conquer, graph algorithms

    Problem solving processes includes some or all of:
    • proposing and winnowing solutions
    • estimating efficiency
    • formulating test plans,
    • problem decomposition,
    • formulating hypotheses
    • debugging
    • isolating effects 
    Specific Course Requirements
    Part of the assessment of this course is the requirement that you complete practice exercises with some frequency and regularity. As such the course expects that you are able to engage in a small to moderate amount of daily effort to complete exercises and reflect on your practice. This frequency and regularity of practice and reflection forms a small but integral part of your assessment.

    It is also expected that you attend lectures, laboratory sessions and practical exams. 
  • 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 CBOK Alignment**

    Code quality Assignment

    12 Individual or Group Formative TBD

    1. 2. 3. 4. 5. 6. 7. 8. 1.1 1.2 2.6 3.1 3.2 4.1 4.2 4.3
    Deliberate practice 30 Individual Formative Weeks 2-12 Min 40% 1. 2. 4. 5. 6. 7. 8. 1.1 1.2 2.6 3.1 3.2 4.1 4.2 4.3
    Lab sessions 6 Individual  Formative Weeks 1-12 1. 2. 3. 7. 8. 1.1 1.2 2.1 2.2 2.3 2.4 2.6 3.1 3.2 4.1 4.2 4.3
    Revision and Reflection quizzes 8 Individual Summative Weeks 2-12 1. 8. 1.1 1.2 2.6 3.1 3.2 4.1 4.2 4.3
    Prac Exams 1,2  24 Individual Formative Weeks 4 and 8 1. 2. 3. 5. 6. 1.1 1.2
    Practical Exam 3 20 Individual Summative Week 12 Min 40% 1. 2. 3. 5. 6. 1.1 1.2
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
    This assessment breakdown complies with the University's Assessment for Coursework Programs Policy.
    This course has two hurdle requirements. Meeting the specified hurdle criteria is a requirement for passing the course.

    **CBOK is the Core Body of Knowledge for ICT Professionals defined by the Australian Computer Society. The alignment in the table above corresponds with the following CBOK Areas:

    1. Problem Solving
    1.1 Abstraction
    1.2 Design

    2. Professional Knowledge
    2.1 Ethics
    2.2 Professional expectations
    2.3 Teamwork concepts & issues
    2.4 Interpersonal communications
    2.5 Societal issues
    2.6 Understanding of ICT profession

    3. Technology resources
    3.1 Hardware & Software
    3.2 Data & information
    3.3 Networking

    4. Technology Building
    4.1 Programming
    4.2 Human factors
    4.3 Systems development
    4.4 Systems acquisition

    5.  ICT Management
    5.1 IT governance & organisational
    5.2 IT project management
    5.3 Service management 
    5.4 Security management
    Assessment Related Requirements
    This course has two hurdles:

    A minimum score of 40% is required in the deliberate practice  section of the course.
    A minimum score of 40% is required for the third practical exam. 

    Failure to achieve these scores 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 60% of laboratory session times (including prac exams). Application for exemptions based on medical and/or compassionate grounds must be made to the course coordinator.
    Assessment Detail
    • Three summative practical exams - on weeks 4,8 and 12 of semester, worth 12%, 12% and 20% respectively
      • Each practical exam has multiple questions of graduated difficulty
      • You need to complete at least one question to pass a exam.
      • Questions are submitted to the automatic assessment system. Instant feedback is given. Multiple submissions are allowed. Partial marks can be granted.
    • One Code Quality Assignment (summative assessment): 12% 
    • Deliberate Practice (summative assessment): 30%
      • Continuous Assessment
      • Consists of Practice Exercise marks and regular journal entries
      • Practice marks are automatically assessed, manual checking of Journal entries.
      • Mark collated at the end of each week for 10 weeks - first collation is at the start of week 3
      • Revision and reflection quizzes (formative assessment): 8%
        • 4 quizzes 
        • MCQ and short essay question covering course content and reflection question on practice and performance
      • Lab participation (formative assessment): 6%
        • 1% attendance/task completion for 6 of the 8 lab sessions
      Practical exams will be submitted via the web submission system.
      Practice exercises and journal entries will be submitted via the web submission system.

      Details of these will be announced in lectures and linked to the course forums.
      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
    • 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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