COSC122-23SU2 (C) Summer Nov 2023 start

Introduction to Computer Science

15 points

Start Date: Monday, 20 November 2023
End Date: Sunday, 11 February 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 3 December 2023
  • Without academic penalty (including no fee refund): Sunday, 14 January 2024


An introduction to Computer Science, including algorithms, complexity and data structures.

The summer version of COSC122 requires you to be on site at Canterbury for an initial block course from November 20 to 27 (2023) and the final exam in February, but the remainder of the course may be taken by self-paced distance study if necessary. Tutoring is available on campus during the summer, but if you are out of town for some of the time, you will have access to online tutoring help. In either case, you will need to be able to work independently. The course is not available as a full distance (D) course. COSC122SU is intended for students who have completed COSC121 or COSC131, and need COSC122 to be able to advance in Software Engineering or 200-level Computer Science.

This course develops a thorough understanding of basic data structures and algorithms that are commonly used in software development, and introduces students to broad concepts from Computer Science that enable them to develop effective programs. A series of labs and assignments will give students practice applying the ideas that they have learnt in lectures. Along the way, students will gain an understanding of why different data structures and algorithms are needed, the applications that they are suited for, and the advantages and disadvantages of their possible implementations.

Learning Outcomes

  • Understand how to analyse algorithms and estimate their worst-case and average-case behaviour (in simple cases).
  • Apply asymptotic complexity ("big-O" notation) as a way of categorising algorithm efficiency.
  • Understand how the algorithm and data structure used to solve a problem will be the main factor in how quickly it is solved.
  • Define, compare, and analyse general algorithmic problem types: sorting, searching, graph algorithms
  • Define, compare and choose between common data structures (linked lists, stacks, queues, hash tables, trees, priority queues, graphs)
  • Implement and empirically compare fundamental algorithms and data structures for practical problems.
  • Understand how algorithms and data structures are applied in other topics in computer science.


Course Coordinator

Tim Bell


The lecture and lab schedule can be confusing to read in the format above; put simply, the week-long block course is scheduled from 9am to 5pm each day (except we finish at 3pm on Friday) the week of 20-27 November 2023, followed by a test on Monday 27 Nov.  This “intensive” week will be a mixture of lectures and lab sessions.  It will be possible, but not ideal, to leave by 4pm during the week.  Apart from this, the only other time you are expected to be on campus is for the final exam, as the rest of the work can be done remotely, with support available from staff online. On campus support will be available, but if you need some flexibility during December and January, this should help with your planning.

Test: 20% - Test at the end of the block course, 1 hour, from 1-2pm on Monday 27 November 2023. This test will count towards your final grade only if it improves your mark.

Assignments: 15%

Lab Quizzes: 10%

Final Test: 55% - To be held onsite at UC on Friday 9 February 2024.

Special arrangements may be possible for sitting off-site if necessary, but students would need to organise these (at their own expense) and such arrangements need to be discussed, and approved, well in advance.

Textbooks / Resources

Required Texts

Miller, Bradley N. , Ranum, David L; Problem solving with algorithms and data structures using Python; Franklin, Beedle & Associates, 2006

This can be bought from the bookshop, and is also available online at no charge at:

Additional Course Outline Information

Academic integrity

Every year several students fail a course because of dishonest practice. Please do not be among them.

You are encouraged to discuss the general aspects of a problem with others. However, anything you submit for credit must be entirely your own work and not copied, with or without modification, from any other person. If you share details of your work with anybody else then you are likely to be in breach of the University's General Course and Examination Regulations and/or Computer Regulations (both of which are set out in the University Calendar) and/or the Computer Science Department's policy (see section 9). The Department treats cases of dishonesty very seriously and, where appropriate, will not hesitate to notify the University Proctor.

If you need help with specific details relating to your work, or are not sure what you are allowed to do, then contact your tutors or lecturer for advice.

Grade moderation

The Computer Science department's grading policy states that in order to pass a course you must meet two requirements:
1. You must achieve an average grade of at least 50% over all assessment items.
2. You must achieve an average mark of at least 45% on invigilated assessment items.

If you satisfy both these criteria, your grade will be determined by the following University-wide scale for converting marks to grades: an average mark of 50% is sufficient for a C- grade, an average mark of 55% earns a C grade, 60% earns a C+ grade and so forth. However if you do not satisfy both the passing criteria you will be given either a D or E grade depending on marks. Marks are sometimes scaled to achieve consistency between courses from year to year.

Students may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control.

Applications for special consideration should be submitted via the Examinations Office website within five days of the assessment.

Where an extension may be granted for an assessment, this will be decided by direct application to the Department and an application to the Examinations Office may not be required.

Special consideration is not available for items worth less than 10% of the course.

Students prevented by extenuating circumstances from completing the course after the final date for withdrawing, may apply for special consideration for late discontinuation of the course. Applications must be submitted to the Examinations Office within five days of the end of the main examination period for the semester.


There are several important documents available online about departmental regulations, policies and guidelines. We expect all students to be familiar with these.  

Notices about this class will be posted to the class forum in the Learn system.

COSC students will also be made members of a class called “CSSE Notices”, where general notices will be posted that apply to all classes (such as information about building access or job opportunities).

Course Outline

The topics covered in lectures will be as follows. The main references are for the current edition of the text book (2nd edition and online). Where a reference is given in square brackets, it is for the first edition.
• Introduction to algorithms, and the relationship with Software Engineering
• Algorithm analysis (Chapter 2 [4])
• Basic data structures – stacks and queues (Chapter 3 [2])
• Lists (Chapter 3 [7])
• Recursion (Chapter 4 [3])
• Searching (Chapter 5 [4])
• Sorting (Chapter 5 [4])
• Trees – binary trees and heaps (Chapter 6 [5])
• Graphs (Chapter 7 [6])
• Overview of major ideas in Computer Science


The course assumes that you are proficient in Python, as taught in COSC121 or COSC131. If you are enrolling in COSC122 but haven't already passed COSC121 or COSC131, you should consult the course supervisor before enrolling.

Indicative Fees

Domestic fee $916.00

International fee $4,750.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Computer Science and Software Engineering .

All COSC122 Occurrences