Design of Algorithms

Description

AIMS Programmers can choose between several representations of data. These will have different strengths and weaknesses, and each will require its own set of algorithms. This subject will cover some of the most frequently used data structures and their associated algorithms. The emphasis will be on justification of algorithm correctness, on analysis of algorithm performance, and on choosing the right data structure for the problem at hand. INDICATIVE CONTENT Sample projects are: approximate string matching for a translation memory, involving sorting and comparison of dynamic programming, branch-and-bound search and brute-force search using a variety of data structures (e.g. arrays, hash tables, tries); speech synthesis based on a pronouncing dictionary and pre-prepared grapheme-phoneme alignment data, based on parsing of the alignment data, hashing of variable length n-grams, and a variety of models for predicting the phoneme(s) associated with a given phoneme sequence (e.g. a simple unigram baseline or a hidden Markov model). Please view this video for further information: Design of Algorithms Teaching Period: 2 March 2026 to 31 May 2026 Assessment Information: Description Timing Percentage Two individual projects during semester, with the first (worth 10%) due in week 6 and the second (worth 20%) due in week 12. Intended Learning Outcomes, (ILOs) 1 to 4 are addressed by the project. 30-35 hours (of work required) Hurdle requirement: Please see below From Week 6 to Week 12 30% One mid-semester test. ILOs 1 and 3 are addressed in the test. 45 minutes Hurdle requirement: Please see below Mid semester 10% One written examination. ILOs 1 to 3 are addressed in the exam. 3 hours Hurdle requirement: Please see below End of semester 60% Additional details Hurdle requirement: To pass the subject, students must obtain at least: 50% overall 15/30 in project work And 35/70 in the mid-semester test and end-of-semester written examination combined.