COSC262-19S1 (C) Semester One 2019

Algorithms

15 points
18 Feb 2019 - 23 Jun 2019

Description

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)
- Graphs: Topological ordering, Minimum spanning trees, Single-source and All-pair shortest paths
- Divide & conquer: design techniques and solving recurrences
- Algorithms for linear time sorting
- Backtracking: combinatorial search and generation
- Computability: reductions and complexity classes
- 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
- String matching: Rabin-Karp algorithm, Knuth-Morris-Pratt algorithm, Boyer-Moore algorithm
- Computational geometry:  Convex hulls (properties, Gift-wrap algorithm, Graham-scan algorithm), Plane-sweep algorithms (closest pair, line intersections), Range search methods (kD trees, Quadtrees)

Learning Outcomes

  • After successful completion of this course, students will be able to:
  • Estimate and analyse the complexity of algorithms
  • Implement algorithm design techniques for solving computational problems
  • Develop algorithms for solving geometrical problems
  • Outline key concepts in pattern matching algorithms
  • Understand and describe the behaviour of algorithms
  • Evaluate the correctness of algorithms
  • Describe and analyse design strategies for solving optimization problems

Pre-requisites

(1) COSC121; (2) COSC122; RP: MATH120

Restrictions

COSC202, COSC229, COSC329

Recommended Preparation

Timetable 2019

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Thursday 14:00 - 15:00 C3 Lecture Theatre 18 Feb - 7 Apr
29 Apr - 2 Jun
02 Thursday 14:00 - 15:00 C2 Lecture Theatre 18 Feb - 24 Feb
Lecture B
Activity Day Time Location Weeks
01 Wednesday 14:00 - 15:00 C3 Lecture Theatre 18 Feb - 7 Apr
29 Apr - 2 Jun
02 Wednesday 14:00 - 15:00 C2 Lecture Theatre 18 Feb - 24 Feb
Lecture C
Activity Day Time Location Weeks
01 Friday 14:00 - 15:00 C2 Lecture Theatre 18 Feb - 7 Apr
29 Apr - 2 Jun
Tutorial A
Activity Day Time Location Weeks
01 Wednesday 11:00 - 13:00 Jack Erskine 340 18 Feb - 7 Apr
29 Apr - 2 Jun
02 Tuesday 09:00 - 11:00 Jack Erskine 340 18 Feb - 7 Apr
29 Apr - 2 Jun
03 Tuesday 15:00 - 17:00 Jack Erskine 445 18 Feb - 7 Apr
29 Apr - 2 Jun
04 Wednesday 09:00 - 11:00 Jack Erskine 340 18 Feb - 7 Apr
29 Apr - 2 Jun
05 Friday 11:00 - 13:00 Jack Erskine 443 18 Feb - 7 Apr
29 Apr - 2 Jun
06 Thursday 16:00 - 18:00 Ernest Rutherford 465 18 Feb - 7 Apr
29 Apr - 2 Jun

Examination and Formal Tests

Test A
Activity Day Time Location Weeks
01 Monday 19:00 - 21:00 Jack Erskine 001 Computer Lab (1/4)
Jack Erskine 010 Computer Lab (1/4)
Jack Erskine 131 Lab 1 (1/4)
Jack Erskine 133 Lab 2 (1/4)
Jack Erskine 134 Lab 3 (1/4)
Jack Erskine 136 Lab 4 (1/4)
Jack Erskine 248 Computer Lab (1/4)
1 Apr - 7 Apr

Timetable Note

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.

Course Coordinator

Kourosh Neshatian

Lecturers

Richard Lobb and Walter Guttmann

Assessment

Assessment Due Date Percentage  Description
Weekly online quizzes 20% Weekly quizzes totalling 20% of the course.
Assignment one super-quiz 5%
Lab test 20%
Assignment two super-quiz 5%
Final Exam 50%

Textbooks

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.

Notes

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).

Additional Course Outline Information

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 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.

Indicative Fees

Domestic fee $850.00

International fee $4,000.00

* 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.

All COSC262 Occurrences

  • COSC262-19S1 (C) Semester One 2019