Program Analysis (G6017)

15 credits, Level 5

Autumn teaching

This module is split into two parts:

Foundations
In the first part of the module, you are introduced to the idea of the asymptotic analysis of algorithms. In particular, you consider the following:

  • specifying a problem
  • the notion of an algorithm and what it means for an algorithm to solve a problem
  • the upper, lower and tight asymptotic bounds associated with an algorithm
  • the best-, worst- and expected-case analysis of an algorithm
  • the lower bound for a problem.

You also consider a number of important data structures, with particular emphasis on priority queues and the generic graph data structure. You look at several basic graph algorithms, in particular:

  • depth-first search of graphs
  • breadth-first search of graphs
  • topological sorting of directed acyclic graphs.

Generic Design Paradigms
In the second part of the module, you consider four of the most important methods used as the basis for algorithm design:

  • greedy methods
  • divide and conquer approaches
  • dynamic programming
  • network flow.

In considering these generic design paradigms, you look at a number of well-known problems, including:

  • interval scheduling
  • single source shortest path
  • minimum spanning tree
  • Huffman codes construction
  • weighted interval scheduling
  • subset sum
  • sequence alignment
  • network flow
  • bipartite matching.

Teaching

100%: Lecture

Assessment

25%: Coursework (Problem Set)
75%: Examination (Unseen examination)

Contact hours and workload

This module is 150 hours of work. This breaks down into 44 hours of contact time and 106 hours of independent study.

This module is running in the academic year 2019/20. We also plan to offer it in future academic years. It may become unavailable due to staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of such changes to modules at the earliest opportunity.

Courses

This module is offered on the following courses: