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This course teaches a range of fundamental algorithms and analyses their properties and behaviour.
Covid-19 Update: Please refer to the course page on AKO | Learn for all information about your course, including lectures, labs, tutorials and assessments.This course teaches a range of fundamental algorithms and analyses their complexity.Algorithms are fundamental to all branches of computer science. They play a key role in the development of efficient computer programs. This course aims to provide a good understanding of fundamental data structures and algorithm design methods used for solving a wide range of problems.A selection of topics from the following (non-exclusive) list is covered:• Introduction to algorithmic thinking and design• Analysis of algorithms (proof techniques, asymptotic notation)• Divide & conquer: recursive design techniques and solving recurrences• Greedy algorithms: Coin changing, Interval scheduling, Fractional knapsack, Huffman codes• Dynamic programming: Top-down approach, Bottom-up enumeration, Optimal substructure, Optimal coin changing, Minimum cost path in grid, Multi-stage graphs, Unbounded knapsack, 0/1 knapsack, Edit distance, Longest common subsequence, Dynamic time warping• Computational geometry: Convex hulls (properties, Gift-wrap algorithm, Graham-scan algorithm), Plane-sweep algorithms (closest pair, line intersections), Range search methods (kD trees, Quadtrees)• Graphs: Topological ordering, Minimum spanning trees, Single-source and All-pair shortest paths• Backtracking: combinatorial search and generation• String matching: Rabin-Karp algorithm, Knuth-Morris-Pratt algorithm, Boyer-Moore algorithm.
Understand the behaviour of algorithms, reason about their correctness, and analyse their complexity.Understand and implement algorithm design paradigms, such as divide and conquer and dynamic programming.Understand and implement a variety of classical algorithms across domains including graphs and computational geometry.Identify an appropriate algorithm for a given problem and implement a solution.
(1) COSC121 or COSC131; (2) COSC122; RP: MATH120
MATH120
Students must attend one activity from each section.
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.
Kourosh Neshatian
Walter Guttmann and Chenyi Zhang
2022 Covid-19 Update: Please refer to the course page on AKO | Learn for all information about your course, including lectures, labs, tutorials and assessments.
Recommended Reading:• Steven S. Skiena, The Algorithm Design Manual, Springer, 2nd Ed., 2008.• Cormen, Leiserson, Rivest, and Stein, Introduction to Algorithms, 3rd Ed., The MIT Press, 2009 • Goodrich and Tamassia, Data Structures and Algorithms in Python, John Wiley & Sons, 2013.
There are several important documents available online about departmental regulations, policies and guidelines at the following site. 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).
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.
Domestic fee $942.00
International fee $4,988.00
* 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 .