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Course Outlines

COMP SCI 7007 - Specialised Programming

North Terrace Campus - Semester 2 - 2025

Computational problem-solving with a focus on group learning and practice. Lecture topics cover general solution categories including: brute-force, divide and conquer, dynamic programming, greedy algorithms and search techniques

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  • General Course Information
    Course Details
    Course Code COMP SCI 7007
    Course Specialised Programming
    Coordinating Unit Computer Science
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 5 hours per week
    Available for Study Abroad and Exchange Y
    Assessment Practical exam and/or assignments
    Course Staff

    Course Coordinator: Dr Orvila Sarker

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

     
    1 Work effectively in problem-solving teams
    2 Develop simple models to solve a variety of real life problems
    3 Apply deliberate practice strategies when learning new skills
    4 Being proficient of coding and testing simple problems

     
    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog 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.

    		 2

    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.

    		 1,2,4

    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.

    		 1

    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

    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.

    		 1

    Attribute 7: Digital capabilities

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

    		 2,3,4

    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
  • Learning Resources
    Required Resources

    All required resources for this course will be provided online via the MyUni platform.

    Recommended Resources
    There are no recommended resources for this course.
    Online Learning
    The course uses online discussion boards to provide help and feedback outside the lecture and practical session.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course aims to improve your programming skills through the introduction and practical applications of a range of programming techniques and the use of deliberate practice. 

    Each week the lecture will introduce a problem solving technique and a set of related problems. During lab sessions students will solve one problem is small groups, then work individually to complete  2 to 3 problems (including the group one) per week. 

    Our objective is to broaden and deepen your skills and experience in programming, increasing code fluency and problem solving. 
    Workload

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

    Students should work an average of 10-12 hours per week on this course. They will practical sessions and some lecture time to design solutions to their problems, and they will need to complete coding and testing outside the class.
    Learning Activities Summary
    Lectures
    Weeks 1-5 foundational computational problem solving including topics in working with groups, string manipulation in java, simulation, brute-force algorithms, recursion and search, simple algorithmic optimisation, sorting-based problems.

    Weeks 6-12 intermediate computational problem solving including, dynamic programming, greedy algorithms and mapping problems to graph algorithms.

    In addition, the second hour of each lecture session will be devoted to group practice and problem solving and presentation of practice portfolios for marking.

    Practice Sessions
    Participation in practice sessions is assessed by handed up written work and/or solution presentation. All students are expected to attend practice sessions.
    Specific Course Requirements
    Students will also be expected to maintain a portfolio of evidence of their practice (recorded both online and/or on paper) that includes the code and a summary of reflections for each 2-week block of practice. 
  • Assessment

    The 最新糖心Vlog'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)*
    		 Learning outcomes CBOK Alignment**
    Weekly Practice 25 Individual Formative Weeks 2-12 3 1.1 1.2 4.1
    Course participation 10 Individual Formative Weeks 2-11 1, 2,4 1.1 1.2 4.1
    Practical Exam1 15 Individual Summative Week 5  2, 4 1.1 1.2 4.1
    Practical Exam2 15 Individual Summative Week 8  2, 4 1.1 1.2 4.1
    Practical Exam3 15 Individual Summative Week 10  2, 4 1.1 1.2 4.1
    Final PracExam  20 Individual Summative Week 12/13  2, 4 1.1 1.2 4.1
    Total 100


    * The specific due date for each assessment task will be available on MyUni.
     
    This assessment breakdown complies with the 最新糖心Vlog's Assessment for Coursework Programs Policy.
     
    This course has a hurdle requirement. 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 最新糖心Vlogn 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
    The course has two hurdles: 
    1. You are required to score a minimum of 40% in your Deliberate Practice component. 
    2. You are required to score a minimum of 40% in the last practical exam. 
    Failure to meet either requirement will result in a capping in your grade at a maximum of 44F.
    Assessment Detail
    Weekly practice is arranged in  5 x 2-week blocks of practice. To get full marks you need to solve a total of 25 problems in the semester and to document your practice with a fortnight reflection summary. 

    Each practical exam will have four problems that covered the solving skills presented during lectures and practical session. To get full marks you need to complete two or three of those problems. 

    Submission
    Submission of answers to practice and prac exam questions will be via Gradescope. You will receive clear and timely notice of all submission details in advance of the submission date.

    Evidence of practice can be collated in your logbook and also summarised in the reflection summaries. Code solution will be subjected to similarity testing through Gradescope or other mechanisms. 
    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 .

  • Student Feedback

    The 最新糖心Vlog 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 最新糖心Vlog 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

    This section contains links to relevant assessment-related policies and guidelines - all university policies.

  • 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.

The 最新糖心Vlog of Adelaide is committed to regular reviews of the courses and programs it offers to students. The 最新糖心Vlog of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
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