COMP SCI 2202 - Foundations of Computer Science

North Terrace Campus - Semester 1 - 2020

This course will develop your coding and problem-solving skills with a focus on data and data science. You will learn algorithm design as well as fundamental programming concepts such as data, selection, iteration and functional decomposition, data abstraction and organisation. You will explore Object-Oriented programming fundamentals, including the use of classes and inheritance. You will build effective problem-solving skills, including exposure to problem solving processes and strategies, simple Searching and Sorting algorithms (linear and binary search, selection and insertion sort). You will build fundamental software development skills including the use of programming environments and tools, debugging, testing and fundamentals of good programming practice, style and design.

  • General Course Information
    Course Details
    Course Code COMP SCI 2202
    Course Foundations of Computer Science
    Coordinating Unit Computer Science
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 6
    Contact Up to 12 hours per week
    Available for Study Abroad and Exchange N
    Incompatible COMP SCI 1007, COMP SCI 1008, COMP SCI 1009, COMP SCI 1101, COMP SCI 1102, COMP SCI 1103, COMP SCI 1201, COMP SCI 1202, COMP SCI 1203, COMP SCI 2103, COMP SCI 2202A, COMP SCI 2202B, ENG 1002, ENG 1003
    Restrictions Available to approved Bachelor of Computer Science students only
    Course Description This course will develop your coding and problem-solving skills with a focus on data and data science. You will learn algorithm design as well as fundamental programming concepts such as data, selection, iteration and functional decomposition, data abstraction and organisation. You will explore Object-Oriented programming fundamentals, including the use of classes and inheritance. You will build effective problem-solving skills, including exposure to problem solving processes and strategies, simple Searching and Sorting algorithms (linear and binary search, selection and insertion sort). You will build fundamental software development skills including the use of programming environments and tools, debugging, testing and fundamentals of good programming practice, style and design.
    Course Staff

    Course Coordinator: Dr Bradley Alexander

    Teaching PeriodCourse Coordinator
    Semester 1
    TBD
    Semester 2
    TBD
    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 Design, implement and test algorithms using fundamental programming constructs and data structures.
    2 Translate between machine level representations and demonstrate how data is represented in computers.
    3 Identify, evaluate and use information sources to support the practice of programming, including APIs, tutorials and documentation.
    4 Complete and compare the runtime complexity of common searching and sorting techniques and their implementations – both iterative and recursive.
    5 Identify and apply searching and sorting techniques (linear and binary search, selection, insertion, merge, quick, bucket sorts).
    6 Identify and apply basic data structures: linked list, stack, queue, qraph, tree (ordered, binary, balanced).
    7 Design, implement and test solutions to problems selecting appropriate data structures and basic algorithmic techiques (brute force, divide and conquer, transform and conquer, greedy).

     
    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   1.5   1.6   2.1   2.2   2.3   3.3   

    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)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1-2
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    1-7
  • Learning Resources
    Required Resources
    There is no required text. The course will make use of various online resources.
    Recommended Resources
    If you prefer to have a textbook for reference, we recommend:

    "Problem Solving with C++", 9e Global Edition, Walter Savitch, ISBN-13:9781292018249, Addison-Wesley, 2015.
    Online Learning
    The School of Computer Science uses a variety of e-learning tools to support traditional face-to-face lectures, tutorials and workshops. These tools provide access to various features including announcements, course materials, discussion boards and assessments for each course of study. Online learning resources can be accessed by selecting your course from http://cs.adelaide.edu.au/degrees-courses/
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course is taught primarily face to face with active practical work interspersed with short examples and discussions. Students are expected to work on practicals and review course material between face to face sessions.
    Workload

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

    As a guide, a 6 unit course comprises a total of 288 hours work (this includes face-to-face contact, any online components, and self directed study).
    Learning Activities Summary
    1. Unix/Subversion basics, use of libraries, variables, constant, string literals, expressions, operators, basic types /representation, conditionals/loops, functions, basic I/O, algorithms and program structure, coding style.
    2. Arrays, vectors and structs, number representation, pointers and dynamic storage, memory allocation and freeing, call by reference, call by pointer, call by value , testing and defensive programming.
    3. Programming languages and paradigms, procedural vs object oriented design, class definitions, class members, class methods / procedures, class implementations.
    4. Overloading operators and methods, copy constructors, static class members.
    5. Class hierarchies, inheritance, multiple inheritance, polymorphism, namespaces.
    6. Recursion, evaluating algorithms memory and runtime, algorithmic approaches to searching (linear and binary), sorting.
    7. Programming data structures: stacks, queues, linked lists.
    8. Trees, algorithmic strategies, review.
  • 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
    Assessments
    Assessment TaskTask TypeTo Be Scheduled DuringWeightingLearning Outcome
    Practicals* Formative Face to face teaching. 20% 1,3,5,6,7
    Theory Quizzes Summative Face to face teaching. 10% 2,3,4,5,6
    Practical Exams Summative Face to face teaching. 10% 1,3,5,6,7
    Final Theory Quiz Summative Final class time. 30% 2,3,4,5,6
    Final Practical Exam Summative Main exam period. 30% 1,3,5,6,7
    Total 100%
    * During practicals, you are encouraged to collaborate with your classmates. This extends to discussing ideas, alternatives, possible solutions and questions about material discussed in class. It does not permit copying of code from classmates. All code you submit must be your own.

    Theory quizzes and practical exams are individual and you must not consult classmates in developing your solutions.

    Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.

    To support the changes to teaching, the following revisions to assessment have been made:

    All quizzes and practical exams including the larger assessments at the end of semester have been moved to online. Submission is as before for practical exams (via web submission). Invigilation arrangements will evolve during the semester as they are trialed and tested.
    Assessment Related Requirements
    Students must achieve a minimum of 40% of the available marks in the Final Theory Quiz and a minimum of 40% of the available marks in the Final Practical Exam. If a student has a final mark for the course greater than 44 F but, fails to achieve both of these requirements, the final mark for the course will be reduced to 44 F.
    Assessment Detail
    Assessment: Practicals* 
    • Weighting: 20%
    • Due Dates: please note schedule on course website. Some practicals will be undertaken during class time but some may be completed outside class times. 
    • Submission Details: Submit using the School of Computer Science Web Submission System.
    • Task: Design, test and implement solutions to programming problems.
    • Scope: These assess your understanding of the course material covered during prior classes. 
    • Criteria by which your assignment will be marked: design, functionality, testing and program style.
    • Learning objectives: 1,3,5,6,7
    Assessment: Theory Quizzes^
    • Weighting: 10%
    • Due Dates: please note schedule on course website. Theory quizzes will be held during class time.
    • Submission Details: Online Quiz.
    • Task: Design, test and implement solutions to the practical problems.
    • Scope: These cover all topics up to the time of the quiz.
    • Criteria by which your assignment will be marked: Correctness of answers.
    • Learning objectives: 2,3,4,5,6
    Assessment: Practical Exams^
    • Weighting: 10%
    • Due Dates: please note schedule on course website. Practical exams will be held during class time.
    • Submission Details: Submit using the School of Computer Science Web Submission System.
    • Task: Design, test and implement solutions to programming problems.
    • Scope: These cover all topics up to the time of the practical exam.
    • Criteria by which your assignment will be marked: design, functionality, testing and program style.
    • Learning objectives: 1,3,5,6,7
    Assessment: Final Theory Quiz^
    • Weighting: 30%
    • Due Dates: The final theory exam will be scheduled during the final class time.
    • Submission Details: Online Quiz
    • Task: The theory exam assesses students depth of knowledge of programming constructs in general, tradeoffs of memory and cpu use in algorithms and data representation.
    • Scope: 60 minute online quiz. Covers material from all of the course.
    • Criteria by which your assignment will be marked: Correctness of answers.
    • Learning objectives: 2,3,4,5,6
    Assessment: Final Practical Exam^
    • Weighting: 30%
    • Due Dates: The final practical exam will be scheduled during the main exam period.
    • Submission Details: Submit using the School of Computer Science Web Submission System.
    • Task: Design, test and implement solutions to programming problems.
    • Scope: 120 minute practical exam. Covers material from all of the course.
    • Criteria by which your assignment will be marked: design, functionality, testing and program style.
    • Learning objectives: 1,3,5,6,7
    Practicals are both summative (assessing your understanding) and formative (used to give you feedback and help you prepare for practical exams). The theory quizzes and practical exams are all summative.

    * During practicals, you are encouraged to collaborate with your classmates. This extends to discussing ideas, alternatives, possible solutions and questions about material discussed in class. It does not permit copying of code from classmates. All code you submit must be your own.

    ^Theory quizzes and practical exams are individual and you must not consult classmates in developing your solutions.
    Submission
    Programming Assignment Submission
    All programming practicals must be submitted using the School of Computer Science Web Submission System. Programming assignments must not be emailed to the lecturer. If you are unable to submit a programming assignment, ask for help.

    Note: programming assignments may be processed using external online plagiarism detection tools. 

    Backup Copy of Programming Assignments
    All programming assignments must be stored in your SVN repository. Failure to use the repository and any subsequent loss of work will not be grounds for an extension.

    Late Penalties
    Failure to submit a programming assignment on time or by the agreed extension deadline will result in penalties. For each day or part-day that a programming assignment is late, the maximum mark that can be awarded is reduced by 25%. The following table shows effect of the capping for different levels of marks:

    Late Penalties - Programming Practicals
    On time MarkOne Day LateTwo Days LateThree Days LateFour Days Late
    100 75 50 25 0
    75 75 50 25 0
    50 50 50 25 0
    25 25 25 25 0
    0 0 0 0 0
    Extensions
    Any request for an extension of time for the submission of a programming assignment should be made well before the due date to the Course Coordinator. Normally, extensions will only be granted for a maximum of two weeks from the original assignment submission date. Extensions will only be granted in cases of genuine extenuating circumstances and evidence, such as a medical certificate, must be provided.

    Theory Quizzes and Practical Exams
    If you are unable to take a theory quiz or attend a practical exam, you must contact the course coordinator as soon as practicable. If appropriate evidence can be provided, such as a medical certificate, alternative arrangements may be considered.
    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.

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