This course is concerned with the study of algorithms for solving practical problems efficiently, and the theoretical analysis of their behaviour. There will also be a brief introduction to complexity theory, the formal study of algorithm performance.
A large variety of algorithms are candidates for study. These include, but are not limited to, the following: greedy algorithms, dynamic programming, network flow algorithms, algorithms for string matching, parallel algorithms, graph algorithms and approximation algorithms.
Upon successful completion, students will have the knowledge and skills to:Upon completion of this course, the student will:
- Analyse a variety of algorithms with practical applications and the resource requirements of each.
- Determine the most suitable algorithm for any given task and then apply it to the problem.
- Demonstrate adequate comprehension of the theory of intractability and prove when certain kinds of problems are intractable.
Assignments (50%); Final Exam (50%)
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WorkloadTwenty-six one-hour lectures, together with occasional seminars
Requisite and Incompatibility
Cormen, Thomas H., Leiserson, Charles E. & Rivest, Ronald L. Introduction to Algorithms, The MIT Electrical Engineering and Computer Science Series. The MIT Press, Cambridge, Massachusetts, 3rd EDdition, 2009.
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Commonwealth Support (CSP) Students
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- 6 units
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