This course is a variation on Programming for Problem Solving (COMP1100 ). It covers the same topics in more depth, requiring addtional contact hours to allow students to deepen their understanding and experience. They will understand the foundations of program semantics, program proof, and implementation of the programming language features that they have learned in the course. As the advanced version of the course the first six Learning Outcomes are the same as for COMP1100.

 

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Apply fundamental programming concepts, using a functional programming language, to solve problems.
2. Understand basic types and the benefits of static typing.
3. Describe, understand and evolve programs, via documentation, testing, and debugging.
4. 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.
5. 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).
6. Understand and apply the concepts of parametric and ad-hoc polymorphism.
7. Reflect on the fundamental mathematical concepts underlying functional programming.
8. Use formal proof and structural induction to reason about the correctness of functional programs.
9. Assessing the significance of different evaluation strategies, including laziness, for the computational behaviour of functional programs.

Recommended Resources

Textbook: Simon Thompson, The Craft of Functional Programming, 3rd edition, Addison-Wesley, 2011. This textbook can downloaded from this Web-site.

Staff Feedback

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, and GitLab.

Student Feedback

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.

Other Information

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.

Use of Generative AI Tools

The use of Generative AI Tools (e.g., ChatGPT) is permitted in this course, given that proper citation and prompts are provided, along with a description of how the tool contributed to the assignment.

Guidelines regarding appropriate citation and use can be found on the ANU library website (https://libguides.anu.edu.au/generative-ai https://libguides.anu.edu.au/generative-ai> <https://libguides.anu.edu.au/generative-ai> <https://libguides.anu.edu.au/generative-ai%3e>)].

Marks will reflect the contribution of the student rather than the contribution of the tools.

Further guidance on appropriate use should be directed to the convener for this course.

However, generative AI will NOT be available to use during the final exam.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Introduction, Sets and Functions, Programming. 1130: Lambda Calculus	Lab: ANU environment, Linux, Haskell
2	Haskell, Basic Types, Algebraic Data Types. 1130: Lambda Calculus	Lab: Gitlab, VSCode, More Haskell
3	Case Expressions, Lists. 1130: Lambda Calculus	Lab: Algebraic Data Types, Pattern Matching, Guards
4	Technical Report Writing, Recursion, Recursion with Lists. 1130: Lambda Calculus	Lab: Cabal and CodeWorld
5	Parametric Polymorphism. 1130: Guest Lecture or No Lecture	Lab: Recursion and Lists
6	Code Quality. 1130: Guest Lecture or No Lecture	Lab: More Lists, Parametric Polymorphism, Recursive Data TypesAssessments: Assignment 1 due at end of teaching breakFormative Assessment: Mid-sem test.
7	Anonymous Functions, Higher Order Functions, Style. 1130: Typed Lambda Calculus	Lab: Style and Testing
8	Ad Hoc Polymorphism, Type Classes. 1130: Typed Lambda Calculus	Lab: Higher Order Functions
9	Search, Trees, Queues, Sets. 1130: Guest Lecture (exact timing depends on availability of guest lecturers)	Lab: Recursion on Trees
10	Complexity. 1130: Typed Lambda Calculus	Lab: Type Classes, Ad Hoc Polymorphism, Binary Search Trees
11	Sorting, Laziness. 1130: Typed Lambda Calculus / Review	Lab: ComplexityAssessment: Assignment 2 Due
12	Review. 1130: No Lecture	Lab: Exam Prep

Tutorial Registration

https://mytimetable.anu.edu.au/even/student

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Programming Assignment 1 (A1)	10 %	14/04/2024	01/05/2024	1,2,3
Programming Assignment 2 (A2)	17 %	19/05/2024	05/06/2024	1,2,3,4
Participation (P)	3 %	24/05/2024	29/05/2024	1,2,3,4,5,6
Final Exam (E)	70 %	30/05/2024	27/06/2024	2,3,4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

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

Assessment Requirements

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

Participation is worth 3% of your course mark.

Examination(s)

The final exam is worth 70% of the course mark. Thus, the final course mark (%) F is calculated as:

F = A1 * 10% + A2 * 17% + P * 3% + E * 70%

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, except where otherwise noted. Material covered in guest lectures (by other than course staff) is not examinable.

Assessment Task 1

Programming Assignment 1 (A1)

Assignment 1 will involve modifying a provided Haskell program and writing a written report. An 1130-specific extension will require you to engage in more creative and difficult programming.

Assessment Task 2

Programming Assignment 2 (A2)

Assignment 2 will involve modifying a provided Haskell program and writing a written report. Marks will also be given for code style and written unit tests. An 1130-specific extension will require you to engage in more creative and difficult programming.

Assessment Task 3

Participation (P)

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.

Assessment Task 4

Final Exam (E)

The Final Exam is a hurdle. You will not pass the course, except perhaps with supplementary assessment, unless you score at least 40% in the final exam.

Academic Integrity

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.

Online Submission

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 CECC Associate Dean (Education). Automated plagiarism detection will be used on all submissions to assist with discovery of possible academic misconduct.

Hardcopy Submission

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

Late submission of assessment items is not permitted without an approved extension. A mark of 0 will be awarded for late submission.

Referencing Requirements

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.

Returning Assignments

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.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

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