Data Structures and Algorithms –Intro

8/12/2019 Data Structures and Algorithms Intro

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Data Structures and Algorithms

Introduction


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Subject Overview

Introduction to many of the basic data structuresused in computer software Understand the data structures

Analyze the algorithms that use them Know when to apply them

Practice design and analysis of data structures.

Practice using these data structures by writing

programs. Make the transformation from programmer to

computer scientist


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Data Structures

Cleverways to organize information in order

to enable efficientcomputation

What do we mean by clever?

What do we mean by efficient?


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Picking the best

Data Structure for the job

The data structure you pick needs to

supportthe operations you need

Ideally it supports the operations you will

use most often in an efficientmanner

Examples of operations:

A Listwith operations insertand delete

A Stackwith operationspushand pop


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Why So Many Data Structures?

Ideal data structure:

fast, elegant, memory efficient

Generates tensions: time vs.space

performance vs.elegance

generality vs. simplicity one operations performance vs.anothers

The study of data structures is the study of

tradeoffs. Thats why we have so many of

them!


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The Need for Data Structures

Data structures organize data

more efficient programs.

More powerful computers

more complexapplications.

More complex applications demand morecalculations.

Complex computing tasks are unlike oureveryday experience.


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Organizing Data

Any organization for a collection ofrecords can be searched, processed inany order, or modified.

The choice of data structure and algorithmcan make the difference between aprogram running in a few seconds ormany days.


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Efficiency

A solution is said to be efficient if it solvesthe problem within its resourceconstraints.

Space

Time

The cost of a solution is the amount of

resources that the solution consumes.


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Selecting a Data Structure

Select a data structure as follows:

1. Analyze the problem to determine theresource constraints a solution must

meet.2. Determine the basic operations that must

be supported. Quantify the resource

constraints for each operation.3. Select the data structure that best meets

these requirements.


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Data Structure Philosophy

Each data structure has costs and benefits.

Rarely is one data structure better thananother in all situations.

A data structure requires:

space for each data item it stores,

time to perform each basic operation,

programming effort.


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Data Structure Philosophy (cont)

Each problem has constraints on availablespace and time.

Only after a careful analysis of problem

characteristics can we know the bestdata structure for the task.

Bank example:

Start account: a few minutes Transactions: a few seconds Close account: overnight


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Terminology

Abstract Data Type (ADT) Mathematical description of an object with set of

operations on the object. Useful building block.

Algorithm A high level, language independent, description of a step-

by-step process

Data structure A specific family of algorithms for implementing an abstract

data type.

Implementation of data structure A specific implementation in a specific language


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Abstract Data Types

Abstract Data Type (ADT): a definition for adata type solely in terms of a set of valuesand a set of operations on that data type.

Each ADT operation is defined by its inputsand outputs.

Encapsulation: Hide implementation details.


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Data Structure

A data structure is the physicalimplementation of an ADT. Each operation associated with the ADT is

implemented by one or more subroutines inthe implementation.

Data structure usually refers to anorganization for data in main memory.

File structure is an organization for data onperipheral storage, such as a disk drive.


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Metaphors

An ADT manages complexity throughabstraction: metaphor. Hierarchies of labels

Ex: transistors gatesCPU.

In a program, implement an ADT, then think

only about the ADT, not its implementation.


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Data Structures

A data structure is a scheme for

organizing data in the memory

of a computer.

Some of the more commonly

used data structures include lists,

arrays, stacks, queues, heaps,

trees, and graphs.Binary Tree


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Data Structures

The way in which the data is

organized affects the

performance of a program for

different tasks.

Computer programmers decide

which data structures to use

based on the nature of the

data and the processes that

need to be performed on that

data.

Binary Tree


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Thank You

Data Structures and Algorithms –Intro

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