School of Computer Science

Module 06-35326 (2020)

Algorithms and Complexity (Extended)

Level 4/M

Paul Levy Rajesh Chitnis Anupam Das Semester 2 20 credits
Co-ordinator: Rajesh Chitnis
Reviewer: Rajesh Chitnis

The Module Description is a strict subset of this Syllabus Page.


Algorithms are at the heart of computer science. In this module we will develop a range of core algorithmic ideas such as dynamic programming, greedy methods, divide-and-conquer techniques, and network flows. We will then learn how to use these to design efficient algorithms for a range of problems, motivated by a range of applications. We will then consider core concepts from computational complexity theory such as NP-completeness, and their implications for algorithm design. Finally, we will consider some advanced modern topics such as approximate and randomized algorithms, parameterized algorithms and complexity, and algorithms for streams of data.

Learning Outcomes

On successful completion of this module, the student should be able to:

  • Understand, explain, and apply core techniques for constructing algorithms
  • Design novel algorithms to solve specific problems
  • Understand and apply core concepts from computational complexity theory
  • Appreciate and explain modern topics in algorithmic theory
  • Demonstrate an awareness of the current literature in this area


  • 06-30175 - Data Structures & Algorithms
  • 06-35324 - Mathematical and Logical Foundations of Computer Science
  • 06-35393 - Theories of Computation

Cannot be taken with


  • Main Assessments: 1.5 hour examination (50%) and continuous assessment (50%)
  • Supplementary Assessments: 1.5 hour examination (50%) and continuous assessment (50%) over the Summer Period

Programmes containing this module