This subject covers a range of important algorithms and data structures. Data structures for implementing containers are covered and include linear structures, tree structures and hash tables. Algorithms for insertion and deletion of elements, and algorithms for searching and sorting on these structures are covered where appropriate. Graphs and graph … For more content click the Read more button below.
This subject covers a range of important algorithms and data structures. Data structures for implementing containers are covered and include linear structures, tree structures and hash tables. Algorithms for insertion and deletion of elements, and algorithms for searching and sorting on these structures are covered where appropriate. Graphs and graph algorithms are also covered. You will learn the construction and workings of the data structures and algorithms covered. They will learn to analyse the effectiveness of each data structure and algorithm for specific problems and categories of problems. You will also implement in programs a wide range of the structures and algorithms covered.
Capstones provide students with a way of integrating and applying knowledge and skills gained throughout their course.
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Academic progress review - Schedule A subject
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Subject instances
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Career ready
Work based learning (placement):No
Graduate capabilities
COMMUNICATION - Communicating and Influencing
COMMUNICATION - Digital Capability
INQUIRY AND ANALYSIS - Creativity and Innovation
INQUIRY AND ANALYSIS - Critical Thinking and Problem Solving
Subject intended learning outcomes
On successful completion you will be able to:
1.
Explain the overall objectives of the field of Algorithms and Data Structures, and the theoretical and experimental techniques for evaluating algorithms and data structures.
2.
Distinguish a range of data structures and searching and sorting algorithms in terms of their mechanism, strengths, weaknesses, and conditions appropriate for the related applications.
3.
Implement a range of data structures and searching and sorting algorithms in Java, whose programs are of high quality in terms of coding style and comments.
4.
Analyse a range of data structures and searching and sorting algorithms in terms of time or space complexity.
5.
Analyse a problem, design a solution, implement it in Java, and evaluate its performance using multiple measures.
