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An introduction to Computer Science, including algorithms, computability, complexity and object-oriented programming.
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.
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.
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Students must attend one activity from each section.
COSC122 involves about 30 hours of lectures, but only 24 hours of lectures are scheduled. The remainder of the lecture time will be through “flipped lectures”, which are videos that you can view online before attending the next class. These are more flexible than scheduled lectures, but you will need to have viewed them to make sense of the next lecture, so please make sure you allow time for this each week. The first week of lectures will be in person, and you’ll be given more information about how these work once lectures start.You need to attend two hours of labs per week. These will be allocated via the online timetable system. Labs begin in the second week of term.Depending on final student numbers, some of the advertised lab/tutorial streams may not run. Final lab/tutorial options will be available for self-allocation closer to the start of the semester through My Timetable.
Miller, Bradley N. , Ranum, David L;
Problem solving with algorithms and data structures using Python;
Franklin, Beedle & Associates, 2006 (2nd edition, unless a new one becomes available during the year).
This can be bought from the bookshop, and is also available online at no charge at:https://runestone.academy/runestone/static/pythonds/index.html.
Library portalCourse Information on Learn
STAR COSC122 Information
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).
Every year several students fail the 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.
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 B- 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.
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 )• Basic data structures – stacks and queues (Chapter 3 )• Lists (Chapter 3 )• Recursion (Chapter 4 )• Searching (Chapter 5 )• Sorting (Chapter 5 )• Trees – binary trees and heaps (Chapter 6 )• Graphs (Chapter 7 )• Overview of major ideas in Computer Science
The course assumes that you are proficient in Python, as taught in COSC121. If you are enrolling in COSC122 but haven't already passed COSC121 or the equivalent, you should consult the course supervisor before enrolling.
Domestic fee $834.00
International fee $3,788.00
* Fees include New Zealand GST and do not include any programme level discount or additional course related expenses.
For further information see
Computer Science and Software Engineering.