The University of Southampton
Courses

# COMP1201 Algorithmics

## Module Overview

This is a core module for computer science and software engineers. It teaches the basic data structures and algorithms which underpins modern software engineering. Without these algorithms most software would be hopelessly slow to the point of unusability. The course also teaches the principles behind the algorithms and data structures and the software engineering lessons which data structures and algorithms teach us.

### Aims and Objectives

#### Module Aims

This module aims to teach the basic data structures and algorithms which underpins modern software engineering, the principles behind the algorithms and data structures, and the software engineering lessons which data structures and algorithms teach us.

#### Learning Outcomes

##### Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• Knowledge of common data structures and algorithms
• Understanding of time complexity
• Understanding of how to code data structures using object oriented methods
##### Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Be able to solve problems algorithmically
##### Subject Specific Practical Skills

Having successfully completed this module you will be able to:

• Have a greater confidence to write programs in Java
• Be able to code a simple data structure
• Be able to use data structures to build complex algorithms
##### Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Choose the most appropriate data structure for a particular problem
• Understand the operation of a number of important computer algorithms using those structures
• Understand how to evaluate an algorithm for efficiency
• Choose an appropriate algorithmic strategy to solve a problem

### Syllabus

Introduction - Data Objects, Data Structures, Complex Data Structures Algorithm Analysis - Time Complexity Algorithm Design and Strategies - Brute Force, Depth-First, Breadth-First, DFID, Best-first, Greedy, Divide and Conquer, - Dynamic Programming, Branch and Bound Simple Data Structures - List, Stack, Queue, Tree, Tree traversal Sorting - Selection Sort, Insertion Sort, Shellsort, MergeSort, QuickSort, Bucket Sort, Radix sort, - External sorting Searching - Sequential Search, Handling Failure, Binary Search, Binary Tree Search, Advanced Tree Structures - AVL Trees, Retaining Balance, Single Rotation, Double Rotation - Splay Trees, Red-black Trees, B-trees Hash tables - Terminology, Hash table size, Hash function collision resolution, Separate chaining, - Open Addressing, Re-hashing Priority Queues (Heaps) - Terminology, Simple implementations, Binary heaps, Heap sort Graphs - Terminology, Adjacency Matrix and List, Connectivity, Breadth vs Depth first search, - Topological sort, Shortest path algorithms, Unweighted graphs, Breadth first search, - Weighted Graphs, Minimum Spanning Tree, Prim's algorithm, Biconnectivity, - Articulation points Geometric algorithms - Convex hull

### Learning and Teaching

TypeHours
Revision10
Tutorial12
Preparation for scheduled sessions18
Follow-up work18
Lecture36
Total study time150

Main M (2005). Data Structures and Other Objects Using Java.

Collins W (2004). Data Structures and the Java Collections Framework.

Weiss MA (2006). Data Structures and Algorithm Analysis in Java.

### Assessment

#### Summative

MethodPercentage contribution
Assessed Tutorials 15%
Exam  (1.5 hours) 50%
In-class Test 35%

#### Referral

MethodPercentage contribution
Exam 100%

#### Repeat Information

Repeat type: Internal & External