CMPT 225Data Structures and Programming

Course Website

http://www.cs.sfu.ca/CC/225/johnwill/

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Assessment

Assignments and labs – 30% Midterm exam in class – 25% Final exam – 45%

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CMPT 225 Topics

Data Structures Algorithms Software Development Programming

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CMPT 225 Topics

Data Structures and Abstract Data Types Stacks Queues Priority Queues Trees Graphs Hash Tables

Algorithms Software Development Programming

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CMPT 225 Topics

Data Structures Algorithms

Tools – Recursion Efficiency – O Notation Algorithms to support data structures Sorting

Software Development Programming

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CMPT 225 Topics

Data Structures Algorithms Software Development

Specification Design – OOP design Implementation Testing

Programming

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CMPT 225 Topics

Data Structures Algorithms Software Development Programming

Implementing data structures and algorithms

Understanding stack and heap memory use

Recursion Writing robust re-usable programs

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Objectives – Data Structures

At the end of this course you should, for each of the data structures we cover, be able to Describe the operations Explain common implementations Implement in a programming language

(C++) Compare with other data structures Recommend which data structure to use

for a given problem

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Objectives – Algorithms

At the end of this course you should, for each of the algorithms we cover, be able to Implement in a programming language

(C++) Analyze running time and space

requirements Compare with other algorithms of a

similar nature

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Objectives – Programming At the end of this course you should be able

to Write algorithms using recursion Understand the advantages of disadvantages of

using recursive algorithms Implement data structures using both arrays and

reference structures as the underlying structure Compare array and reference structure

implementations Use features of the C++ language to write well-

structured programs

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Objectives – O Notation

At the end of this course you should be able to Understand and describe the

mathematical basis of O notation Compute the O notation running time of

algorithms Understand the limitations of O notation

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Overall Objectives

Develop problem solving techniques To take a problem statement And develop a computer program to

solve the problem A solution consists of two

components Algorithms Data storage

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Course Focus

Problem solving Use abstraction to design solutions Design modular programs Use recursion as a problem-solving

strategy Provide tools for the management of

data Identify abstract data types (ADTs) Examine applications that use the ADTs Construct implementations of the ADTs

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What Makes a Good Solution?

A good solution is cost effective We should minimize the cost of the software

Running costs Resources (computing time and memory) Interaction costs (e.g. poor GUI may result in the

loss of business) Costs related to errors (e.g. loss of customer

information, storing incorrect data, etc.) Development and maintenance costs

i.e. costs related to the software life cycle

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Good Software Is

Well structured Modular Modifiable Written with good style

Well documented Easy to use Efficient Able to degrade gracefully (fail-safe) Debugged

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Software Life Cycle

Documentation

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Software Life Cycle Phases - 1 Specification

Understand the client’s problem and requirements Ensure that the requirements are clear and complete and

understood by all stakeholders Design

Plan the implementation of the application’s data and operations

Plan the testing Risk Analysis Verification

Ensure that algorithms are correct Ensure that the design satisfies the requirements

(validation) Implementation

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Software Life Cycle Phases - 2 Testing

Verify that the code works and meets the client’s requirements

There are various types of testing, unit testing, integration testing, system testing, user acceptance testing

Refining Production

Package, distribute and install application and train users Maintenance

Add features, and Fix bugs

Documentation, which includes the user manual Common to all the phases of the life cycle

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Software Life Cycle and CMPT 225

We are primarily concerned with three phases of the life cycle Design Implementation Testing