2021/22 Undergraduate Module Catalogue
COMP2721 Algorithms and Data Structures II
10 creditsClass Size: 500
Module manager: Dr Haiko Muller
Email: h.muller@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2021/22
Pre-requisites
COMP1421 | Fundamental Mathematical Concepts |
COMP1511 | Introduction to Discrete Mathematics |
Module replaces
COMP2541This module is not approved as a discovery module
Module summary
This module focuses on key algorithms and data structures, that form the toolkit of a modern computer specialist. There may exist several algorithms for solving the same problem, and it is important to produce the one which is efficient in terms of the computation time and space requirements. Our primary goal is to identify the most efficient solutions among those available and to provide a formal justification of that choice. Practicing with advanced algorithms and data structures students will learn how to combine them in order to produce an efficient solution approach. The algorithm design methods (Greedy algorithms, dynamic programming, divide and conquer) will be illustrated by various examples. Advanced Data Structures (priority queues, dictionaries) and their implementations will be considered.Objectives
On completion of this module, students should be able to:- Understand the fundamental techniques for the design of efficient algorithms (greedy algorithms, dynamic programming, divide and conquer);
- Demonstrate how these algorithms are analysed;
- Understand advanced data structures (priority queues, dictionaries), their efficient implementation and applications;
- Understand how these algorithms and data structures relate to the central practical problems of modern computer science.
Learning outcomes
On completion of the year/programme students should have provided evidence of being able to:
-demonstrate a broad understanding of the concepts, information, practical competencies and techniques which are standard features in a range of aspects of the discipline;
-apply generic and subject specific intellectual qualities to standard situations outside the context in which they were originally studied;
-appreciate and employ the main methods of enquiry in the subject and critically evaluate the appropriateness of different methods of enquiry;
-use a range of techniques to initiate and undertake the analysis of data and information;
Syllabus
Principles of algorithm design:
Representations of graphs: adjacency list, adjacency matrix. Depth- and breadth-first search traversals, shortest-paths algorithms (Dijkstra's and Floyd/Warshall algorithm), minimum spanning tree (Prim's and Kruskal's algorithms). Algorithmic strategies: greedy algorithm, dynamic programming (CYK algorithm), divide-and-conquer. Recurrence equations, Master theorem. Strassen's algorithm for matrix multiplication.
Abstract data types:
priority queues and their implementations (binary heaps, binomial heaps)
dictionaries and their implementations (hash tables and balanced search trees)
Teaching methods
Delivery type | Number | Length hours | Student hours |
Class tests, exams and assessment | 1 | 2.00 | 2.00 |
Lecture | 22 | 1.00 | 22.00 |
Tutorial | 10 | 1.00 | 10.00 |
Private study hours | 66.00 | ||
Total Contact hours | 34.00 | ||
Total hours (100hr per 10 credits) | 100.00 |
Private study
Taught session preparation: 18 hoursTaught session follow-up: 18 hours
Self-directed study: 7 hours
Assessment activities: 23 hours
Opportunities for Formative Feedback
Four pieces of coursework should provide timely feed-back to students about their progress.Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
Report | worksheets/exercises that will be provided either via gradescope and will have multiple choice but also normal questions | 12.00 |
Report | worksheets/exercises that will be provided either via gradescope and will have multiple choice but also normal questions | 12.00 |
Report | worksheets/exercises that will be provided either via gradescope and will have multiple choice but also normal questions | 16.00 |
Total percentage (Assessment Coursework) | 40.00 |
This module will be reassessed by an online time-constrained assessment.
Exams
Exam type | Exam duration | % of formal assessment |
Online Time-Limited assessment | 48 hr 00 mins | 60.00 |
Total percentage (Assessment Exams) | 60.00 |
This module will be reassessed by an online time-constrained assessment.
Reading list
The reading list is available from the Library websiteLast updated: 15/03/2022 16:12:19
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