- Class Number 7394
- Term Code 3260
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Michael Norrish
- Donovan Crichton
- Class Dates
- Class Start Date 25/07/2022
- Class End Date 28/10/2022
- Census Date 31/08/2022
- Last Date to Enrol 01/08/2022
This course is the first of three core computer science courses on programming. It introduces students to the field of computer science as a discipline for solving problems through computation and provides the foundation for more advanced courses on programming and software development. Data structures and algorithms, the key concepts at the core of computer science, receive their first treatment in this course.
The course covers functional programming in depth, developing the core idea of functions operating on data structures. Students learn the organization of programming languages using types, how programs are evaluated (reduction), functional composition, recursive functions, algebraic data types, pattern matching, parametric polymorphism, higher-order functions. Students also gain exposure to asymptotic analysis of basic data structures, abstract data types, modules, laziness, and streams. The functional paradigm demonstrates elegant solutions to many programming problems.
The course also introduces students to standard productivity tools for software development that will be used throughout the course and remainder of the computer science degree. These include distributed software revision control systems.
The Advanced version of this course covers these topics in more depth, allowing students to deepen their understanding and experience.
Upon successful completion, students will have the knowledge and skills to:
- Apply fundamental programming concepts, using a functional programming language, to solve problems.
- Understand basic types and the benefits of static typing.
- Describe, understand and evolve programs, via documentation, testing, and debugging.
- Discuss, use, and apply the fundamentals of data structures, algorithms, and design; create, implement, and debug algorithms for solving problems, including recursively, using divide-and-conquer, and via decomposition.
- Discuss basic algorithmic analysis for simple algorithms; determine appropriate algorithmic approaches to a problem (for example bruteforce, greedy, divide-and-conquer, recursive backtracking, heuristic, dynamic programming).
- Understand and apply the concepts of parametric and ad-hoc polymorphism
Examination Material or equipment
Open book exam, but communication with others during the exam is strictly prohibited. Exam conditions may vary depending on covid-related rules that exist at the time.
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus groups
- online via course forums, Wattle, GitLab, and GradeScope.
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.
This course does allow for collaboration if your collaborators are explicitly mentioned in your submission and some additional rules are followed:
- The writing of code and documentation that you intend to submit must always be done entirely by you, and you only.
- You may exchange ideas on scrap paper, boards, and the like, but do not work together on documents (e.g., reports or code) that are intended for submission.
- Do not collaborate or communicate with other students about your submission right before you start writing your submission documents.
- Leave some time to digest your discussions with others before working on your submission.
A student in this course is expected to be able to explain and defend their submitted assessment items. The course convener may conduct or initiate an additional interview about any submitted assessment item for any student in the course. Any significant discrepancy between the submitted assessment and interview may trigger further investigation.
|Week/Session||Summary of Activities||Assessment|
|1||Introduction, Sets and Functions, Programming||Lab: The ANU Computing lab environment, Linux, the Glasgow Haskell Compiler Interactive read-eval-print-loop (GHCi)|
|2||Haskell, Basic Types, Algebraic Data Types||Lab: Gitlab, Interactive Development Environment, Functions|
|3||Case Expressions, Lists||Lab: Algebraic Data Types, Pattern Matching, Guards|
|4||Technical Report Writing, Recursion, Recursion with Lists||Lab: Cabal and the CodeWorld API for interactive graphics|
|5||Parametric Polymorphism||Lab: Recursion on Lists Assessment: Engagement Hurdle, Assignment 1 Indicative Part A due|
|6||Code Quality||Lab: More Lists, Parametric Polymorphism, Recursive Data Types Assessments: Midterm exam (exact date may vary based on exam schedule), Assignment 1 due first week of teaching break|
|7||Anonymous Functions, Higher Order Functions, Style||Lab: Style and Testing|
|8||Ad Hoc Polymorphism:n Type Classes||Lab: Higher Order Functions Assessment: Assignment 2 Due|
|9||Search, Trees, Game Trees||Lab: Recursion on Trees|
|10||Alpha-Beta Pruning, Complexity||Lab: Type Classes, Ad Hoc Polymorphism, Binary Search Trees|
|11||Sorting, Laziness||Lab: Complexity|
|12||Review||Lab: Exam Prep Assessment: Assignment 3 Due|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Programming Assignment 1 (A1)||10 %||15/09/2022||02/10/2022||1,2,3|
|Programming Assignment 2 (A2)||12 %||06/10/2022||23/10/2022||1,2,3,4|
|Programming Assignment 3 (A3)||15 %||03/11/2022||18/11/2022||1,2,3,4,5,6|
|Participation (P)||3 %||02/10/2022||05/10/2022||1,2,3,4,5,6|
|Mid-Term Exam (M)||10 %||24/08/2022||30/08/2022||1,2,3|
|Final Exam (E)||50 %||*||*||1,2,3,4,5,6|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:
- Academic Integrity Policy and Procedure
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Guideline and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
- Code of practice for teaching and learning
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Participation is worth 3% of your course mark. Attending and participating in 4 of the first 5 labs will result in the Engagement Hurdle being waived. Alternatively, achieving a mark of at least 30% on the mid-term exam satisfies the Engagement Hurdle. Failure to satisfy the Engagement Hurdle will result in a grade of NCN. The Engagement Hurdle may only be waived following granting of Special Consideration.
There will be two exams: a mid-term exam and a final exam. The mid-term exam is worth 10% of the course mark and is redeemable via the final exam. The final exam is worth 50% of the course mark. The final exam is worth 50% of the course mark. Thus, the final course mark (%) F is calculated as:
F = A1 x 10% + A2 x 12% + A3 x 15% + P x 3% + max(M,E) * 10% + E x 50%
where A1, A2, A3, P, M, E are the percentage of the available marks achieved for each assessment item.
Examinable material comprises the contents of lectures, labs, and assignments, as well as the relevant chapters of the textbook. Material covered in guest lectures (by other than course staff) is not examinable.
Assessment Task 1
Learning Outcomes: 1,2,3
Programming Assignment 1 (A1)
Assignment 1 contains a Part A which you will be asked to submit earlier than the rest of the assignment. Tutors will return feedback for this along with an indicative mark. This mark will not be used to calculate your final mark on the assignment, allowing you to use this feedback to improve your full assignment. We strongly recommend you make use of this feedback loop. Assignment 1 will involve modifying a provided Haskell program, and a written report.
Assessment Task 2
Learning Outcomes: 1,2,3,4
Programming Assignment 2 (A2)
Assignment 2 will involve modifying a provided Haskell program, and a written report. Marks will be given for code style and written unit tests. The primary programming technique assessed in this assignment will be recursion.
Assessment Task 3
Learning Outcomes: 1,2,3,4,5,6
Programming Assignment 3 (A3)
Assignment 3 will involve modifying a provided Haskell program, and a written report. Marks will be given for code style and written unit tests. This assignment will ask that you show some creativity in designing a program that excels at a given task.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6
Participation marks are gained in the labs; students get one mark for each lab they participate in by actively engaging and demonstrating (this requires attendance), and one mark for submission of genuine attempts at each set of lab exercises. Note that only the first of these marks (across the first five labs) will be used to waive the Engagement Hurdle (see the Mid-Term Exam assessment for details). Your marks will be counted from your ten best labs.
Assessment Task 5
Learning Outcomes: 1,2,3
Mid-Term Exam (M)
The mark for the Mid-term Exam is redeemable via the Final Exam. The Mid-Term Exam is worth 10% of your course mark.
The mid-term exam is a hurdle, passed by achieving at least 30%. However, because this is an introductory course, we will waive this hurdle for any student who can demonstrate their engagement with the course by attending and participating (see the Participation assessment for details) in at least four of the first five labs. Because this hurdle can be achieved via engagement we call this hurdle the Engagement Hurdle, and strongly suggest that you avoid this hurdle by attending and participating in labs.
Assessment Task 6
Learning Outcomes: 1,2,3,4,5,6
Final Exam (E)
In order to pass the course after the final exam, students must get a minimum final mark of 40% across the course and pass the Engagement Hurdle and pass the Final Exam Hurdle by getting at least 40% on the final exam. Final marks are moderated within the course and by a School of Computing examiners meeting. Students receiving a final mark of 45%-49%, or who would have received 45% were it not for failing a hurdle, will be offered supplementary assessment as per ANU rules. The Final Exam is worth 50% of your course mark, or 60% if your mid-term exam mark is lower.
Given that exams will be held online on your personal computer, we will need to gain assurance that students' exams have been conducted with academic integrity. To ensure this, all students will attend a short interview with tutors where they answer simple questions about their exam answers. If students cannot answer these questions, an initial review process will begin to investigate whether a breach of academic integrity, such as plagiarism, has occurred. The result of this investigation has potential to effect your final exam mark.
Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.
The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.
The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.
The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.
Submission of labs and programming assignments will be via the ANU CECS Teaching GitLab (https://gitlab.cecs.anu.edu.au/) as approved by the CECS Associate Dean (Education).
Exams will also use online submission of free-form text, scans of handwritten text, questions and answers via Web-based forms, and answers to programming questions, via online systems including Wattle (https://wattle.anu.edu.au), ANU CECS GitLab (https://gitlab.cecs.anu.edu.au), or GradeScope (https://gradescope.com), as approved by the CECS Associate Dean (Education).
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Late submission of assessment items is not permitted without an extension requested in writing on or before the due date. A mark of 0 will be awarded for late submission.
The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.
Assignment marks and feedback will given online.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Resubmission of Assignments
Resubmission of assignments will not be permitted without grant of Special Consideration.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Access and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students