Data Structures and Algorithms

By Alison Cawsey
This course will have two main sections. The first, shorter section will introduce inheritance and polymorphism in object oriented programming. This is material makes the implementation of some datastructures more elegant and more re-useable. However this section of the course is fairly independent of the next. The second, longer section will look at different sorts of algorithms, and in particular string processing algorithms and graph algorithms.
There are various concepts from Data Structure & Algorithms which will be assumed. The basic idea of an abstract datatype is important. You also need to be familiar with pointers for some of the first section. You should also be able to implement and use a stack and a queue (with or without the help of a textbook).
Why should you want to know about algorithms? There are a number of possible reasons:
  • To avoid re-inventing the wheel. As you might expect, for many programming problems, someone has already developed a good algorithm to solve that problem. For many of these algorithms, people have formally analysed their properties, so you can be confident in their correctness and efficiency. For example, we know that merge sort and quick sort both work correctly, and have average case complexity O(n log n), so we can straightforwardly use either algorithm in our programs. We might be able to further choose between these two algorithms, depending on properties of our data (is it already almost sorted?).
  • To help when developing your own algorithms. Many of the principles of data-abstraction and algorithm design, illustrated by some of the algorithms discussed here, are important in all programming problem. Not all tasks have ``off-the-shelf'' algorithms available, so you will sometimes have to develop your own. Merge sort illustrates a widely applicable technique: split the problem in two, solve each separately, then combine the results. A knowledge of well known algorithms will provide a source of ideas that may be applied to new tasks.
  • To help understand tools that use particular algorithms, so you can select the appropriate tool to use. For example, documentation of various compression programs will tell you that pack uses Huffman coding, compress uses LZW, and Gzip uses the Lempel-Ziv algorithm. If you have at least some understanding of these algorithms you will know which is likely to be better and how much reduction in file size you might expect for a given type of file (e.g., does the file involve a lot of repetition of common sequences of characters).
  • Because they're neat. Many surprisingly simple and elegant algorithms have been invented. If you have even a slightly Mathematical disposition you should find them interesting in their own right.

For all these reasons it is useful to have a broad familiarity with a range of algorithms, and to know what they may be used for.

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