This module will reinforce the programming concepts that were taught in the autumn semester's programming module while exploring essential data structures and algorithms. This includes a particular focus on algorithms used in traditional AI. Students will also learn to analyse the efficiency of algorithms and data structures, and make informed choices about these for practical problems.

• Programming Assignment
• Final examination

• Blackboard
• Unconfirmed practical marks when available

The aims of this module are:

• To reinforce existing programming knowledge through implementation of common algorithms.
• To demonstrate the implementation and analysis of algorithms commonly seen in the computing sciences.

By the end of the module, the student will be able to:

• Describe data structures and algorithms that are commonly used in computational solutions.
• Implement these data structures and algorithms to provide computational solutions to problems.
• Analyse the efficiency of algorithms.
• Select appropriate data structures and algorithms to be used in the solutions for specific scenarios.

Typical topics (subject to variation) include:

• Algorithms as a technology
• Efficiency of algorithms
• Design and Analysis of Algorithms for Sorting
• Insertion sort
• Heap sort
• Mergesort
• Quicksort
• Linear time sorting
• Data Structures
  • Stacks and Queues
  • Linked lists
  • Binary search trees
  • Balanced trees
  • Graphs
• Design and Analysis of Graph Algorithms
  • Searching in graphs
  • Finding shortest paths in graphs
  • Combinatorial graph problems
• Algorithmic Design Paradigms 
  • Greedy algorithms
  • Divide and conquer
  • Dynamic programming

Students will receive feedback on work carried out in the lab sessions. Additionally, demonstration sessions will give generic feedback on lab tasks. A number of automated quizzes will help students self assess their understanding and help guide their self study.