KV5033 - Algorithms and Data Structures

Concepts, principles and techniques will be introduced to you in lectures, and you will explore these further in guided practical exercises in laboratory/workshop sessions. You will work on these during workshops and hands-on sessions in Northumbria’s CIS building computer labs, which are fully equipped with the latest industry-standard software. You will also be provided with guided independent learning materials. When appropriate, examples will be taken from real business and industrial situations. Throughout the module you will be given the opportunity to examine and discuss the use of algorithms and data structures development in real and simulated situations.

You will be supported by lecturers during the timetabled sessions when you will receive feedback on your work. In the laboratory/workshop sessions you will get guidance on your studies of the subject and an opportunity to ask questions arising from them. Most importantly, you will get feedback on your work and your progress, including on the practical exercises. The University’s e-Learning Portal offers remote access to all lecture and workshop/seminar materials to reinforce your learning and include model answers to exercises to help assess your own work. In addition, the university library offers support for all students through providing electronic resources.

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

Knowledge & Understanding:
MLO1 – A critical understanding of collection classes and be able to implement data structures such as lists, queues and trees together with algorithms to process these structures (e.g. searching and sorting)
MLO2 – A critical application of algorithm complexity and the big-O notation, including algorithms for AI and data security, and use this to select suitable data structures for a particular scenario

Intellectual / Professional skills & abilities:
MLO3 – Identify problems and select and apply effective algorithms, data structures models for their solution.
MLO4 – Demonstrate critical computational thinking for the algorithms and data structures their professional issues and relevance to everyday life.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
MLO5 – Demonstrate critical engagement with Contemporary Algorithms research and raise awareness of ethical, social, cultural and legal issues.

The main element of summative assessment (100%) will be a final assignment and an individual work. This will be a real-world scenario-based object-oriented programming task to explore aspects of an implementation of algorithms. This will include making an appropriate selection of data structures. You will be required to submit a code along with reflective technical report. The word limit for the reflective technical report will be 2500 words. You will receive both informative and confirmatory feedback on your assessment.
This assessment addresses Module Learning Outcomes – MLO1, MLO2, MLO3, MLO4, MLO5

There will also be formative class tests which will take place within the teaching weeks which will be week 9 and week 10.
This formative assessment addresses Module Learning Outcomes – MLO1, MLO2, MLO4
On an on-going basis you will also receive formative feedback on exercises you are required to complete.

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This module introduces you to the algorithms’ theory, principles and practice behind data structures. Indicative topics include introduction to algorithms, big-O notation, searching, sorting and a number of fundamental data structures, including arrays, array lists, linked lists, stacks, queues, trees, sets, hash maps, dictionary, graphs, dynamic programming and concurrent programming. These data structures are covered via the notion of Abstract Data Types, and concretely in terms of their implementation in an object-oriented framework.

Theory is followed by practical workshops where you will be introduced to applying the appropriate data structures to make your code faster and scalable and apply them to high performance computing. You will apply the acquired theoretical and practical knowledge in building a substantial software solution.