This module is a fundamental core element of the degree for current 4th year students. It is constituted by research on a topic derived from the field of...

This module is a fundamental core element of the degree for current 4th year students. It is constituted by research on a topic derived from the field of specialisation of each student. The theme of the Dissertation is chosen during the second year in discussion with ESPS tutors and course teachers. Dissertation Guidelines are available on Moodle. You may also find it useful to consult dissertations from previous years in the ESPS Library. Please note, for students taking a Full Economics specialism, the Dissertation is an optional module. Compulsory for final year ESPS (exception: full economics specialists).

The aim of the dissertation project is to undertake a sustained enquiry into a specific theoretical, empirical, or policy issue in economics. You will...

The aim of the dissertation project is to undertake a sustained enquiry into a specific theoretical, empirical, or policy issue in economics. You will integrate and apply the critical thinking, knowledge, and methods developed in the core and options taught modules and present your findings in a written, word-limited academic research paper. Your project will require you to refine an interest into to a viable question, situate it within the existing academic literature, justify your intellectual and methodological approach to its investigation, and carry out your investigation using formal economic theory, quantitative tools and data analysis, or a combination of both. You will demonstrate your ability for lightly supervised research, time and task management, and effective written communication with an academic audience.

Aims:

To introduce more formal aspects of algorithms and data structures, techniques for analysing the complexity of algorithms, and to discuss the limits of...

Aims:

To introduce more formal aspects of algorithms and data structures, techniques for analysing the complexity of algorithms, and to discuss the limits of computation (intractable and undecidable problems).Learning outcomes:
On successful completion of the module, a student will be able to:

Understand how to use a variety of data structures.
	Understand a variety of common algorithms and why some are more efficient than others
	Carry out time complexity analysis in a variety of scenarios.
	Discuss intractable and undecidable problems.
Content:

Course Introduction:
Algorithms and Data Structures:

Why study algorithms and data structures?
	Pseudocode.
	Efficiency of algorithms.
	Recursion.
	Arrays.
	Approaches to algorithm design including greedy and divide and conquer.
	Graph traversal.
Analysis of Algorithms:

Empirical vs theoretical analysis.
	Algorithmic complexity.
	O-notation.
	Forms of time complexity analysis (worst case, average case, best worst case).
	Sums of series and simple summation formulae.
	Recursive algorithms and recurrence relations.
Limits of Computation:

Tractable and intractable problems.
	The complexity classes P, NP, NPC.
	Undecidability.
Requisites:

To be eligible to select this module, a student must: (1) be registered on a programme and year of study for which it is a formally available; and (2) have also selected Introductory Programming (COMP0066), App Engineering (COMP0067), and Computer Architecture and Operating Systems (COMP0068).