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Unit information: Advanced Algorithms (Teaching Unit) in 2022/23

Please note: It is possible that the information shown for future academic years may change due to developments in the relevant academic field. Optional unit availability varies depending on both staffing, student choice and timetabling constraints.

Unit name Advanced Algorithms (Teaching Unit)
Unit code COMS30042
Credit points 0
Level of study H/6
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Clifford
Open unit status Not open

COMS10017 Object-Oriented Programming and Algorithms I or equivalent.

COMS20010 Algorithms II or equivalent.

Solid understanding of O-notation and recurrence relations, the “greedy”, “divide-and-conquer” and “dynamic programming” paradigms of algorithm design, proof by induction and contradiction, discrete probability.

Previous exposure to pseudocode.

A solid understanding of arrays, linked lists, and priority queues.


COMS30041 Advanced Algorithms (10 credit exam assessment unit).

School/department Department of Computer Science
Faculty Faculty of Engineering


This unit gives an overview of recent advances in the design of algorithms and data structures. These fall into two broad categories.

First, we will cover algorithms and data structures for fundamental problems surrounding storing, recovering and searching within data. For these problems we will see that nearly optimal solutions are possible.

Second are optimisation problems where sometimes only exponential-time algorithms are known. We will discuss when these problems admit exact efficient solutions, and when only approximation is possible.

Intended learning outcomes

On successful completion of this unit, students will:

  1. Be able to apply sophisticated analysis techniques to measure the time and space complexity of algorithms and also prove their correctness.
  2. Demonstrate a clear understanding of a variety of advanced data structures and their applications.
  3. Be aware of and able to apply standard approaches to approximating the answer to (NP-complete) problems where finding the exact answer is infeasible.

Teaching details

Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, problem sheets and self-directed exercises.

Teaching will take place over Weeks 1-7, with consolidation and revision sessions in Weeks 11 and 12.

Assessment Details

Exam (January, 100%).


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