COMPSCI 130 : Introduction to Software Fundamentals


2024 Summer School (1240) (15 POINTS)

Course Prescription

Fundamental programming techniques and processes, such as conditionals, iteration, recursion, functions, testing and debugging. Efficient ways to organise and manipulate data, including sorting and searching algorithms. Writing software that uses and implements common abstract data types such as lists, stacks, queues, dictionaries and trees. Prerequisite: COMPSCI 101, or B+ or higher in ENGGEN 131, or Achievement Standard NCEA Level 3 Digital Technologies and Programming: 91906 Use complex programming techniques to develop a computer program, or 91637 Develop a complex computer program for a specified task

Course Overview

This is the entry course to Computer Science for students with prior programming experience. It focuses on the quality of processes used when developing software, and the quality of the software product produced using those processes. The course provides an introduction to fundamental software development techniques and processes, such as reading, writing, and documenting programming code, decomposing problems, testing, debugging, using recursion and handling unexpected errors. It also addresses efficient ways to organize and manipulate data, including sorting and searching algorithms, and writing software that uses and implements common abstract data types such as lists, stacks, queues, dictionaries and trees. The course will be taught using the Python programming language.

Course Requirements

Restriction: COMPSCI 105, 107

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Capability 7: Collaboration
Capability 8: Ethics and Professionalism
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Decompose a problem into several smaller tasks, design and implement a function for each task, and compose these functions. (Capability 3, 4 and 5)
  2. Export and import data structures (via file or console I/O) using standard text-based data formats. (Capability 3)
  3. Use common programming statements to implement iterative and recursive algorithms. (Capability 3 and 5)
  4. Use simple testing and debugging strategies to correct faulty programs. (Capability 3 and 5)
  5. Demonstrate how typical data structures are modelled in memory. (Capability 3 and 4)
  6. Provide a useful level of documentation for all programs developed. (Capability 3, 6 and 8)
  7. Work together with peers to collaboratively develop, and review, programs. (Capability 6, 7 and 8)
  8. Write programs that use standard abstract data types (lists, stacks, queues, priority queues, dictionaries). (Capability 3, 4 and 5)
  9. Implement standard abstract data types using standard data structures such as arrays, linked lists, hash tables and trees. (Capability 3 and 5)


Assessment Type Percentage Classification
Labs & Assignments 30% Individual Coursework
Test 20% Individual Test
Test2/Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8 9
Labs & Assignments

To pass the course, as well as obtaining at least 50% overall, a student must also pass the Test + Test2/Exam component (70%) by obtaining at least 35 out of 70 and pass the Practical (Labs + Assignments) component (30%) by obtaining at least 15 out of 30.


Tuākana Science is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at

For more information and to find contact details for the Computer Science Tuākana coordinator, please see
The School of Computer Science Tuākana programme provides support for this course. See:

Key Topics

  • Topic 1: Python revision
  • Topic 2: Software maintenance, modularity, testing and exceptions
  • Topic 3: Complexity of programs, Big O
  • Topic 4: Sorting and searching
  • Topic 5: Abstraction; Classes, and Abstract Data Types
  • Topic 6: Stacks and Queues
  • Topic 7: Recursion
  • Topic 8: linked Lists
  • Topic 9: Trees
  • Topic 10: Binary Search Trees
  • Topic 11: Hashing
  • Topic 12: Priority Queues and Heaps

Special Requirements

There will be one (mid-semester) test. The test will be on CodeRunner and will assess programming ability. The test2/exam will also be on CodeRunner and will assess the understanding of concepts related to data structures as well as programming ability.  

To pass the course, as well as obtaining at least 50% overall, a student must also pass the Test + test2/Exam component (70%) by obtaining at least 35 out of 70 and pass the Practical (Labs + Assignments) component (30%) by obtaining at least 15 out of 30.

Workload Expectations

This course is a standard 15-point course and students are expected to spend 10 hours per week involved in each 15-point course that they are enrolled in. 

For this course, each week, you can expect: 

  • 1 one-hour lecture
  • 4 two-hour labs
  • 4 hours of reading and thinking about the content 
  • 7 hours of work on programming practice and/or test and exam preparation

Delivery Mode

Campus Experience

Laboratories will be held on campus.
Lectures will be held on campus and will also be available as recordings. 
The course will not include live online events.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

This course assumes you know how to program, but makes no assumption about the programming language that you know. The course is taught in Python and includes a short overview of Python syntax at the beginning of the course. To revise your Python knowledge, the following online text is recommended:
The text for COMPSCI 130 can be located at:

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Based on feedback from students last semester, the labs for the course will now be released two days before the actual lab day and will be due at 11:59pm (NZ Time) on the day of the lab. 

Other Information

Please contact the course coordinator if you have any queries or concerns.  You can find their contact details on the home page of the course's Canvas pages.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Contact details for the class rep(s) will be available on the course's home page on Canvas.


The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 06/11/2023 08:36 a.m.