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Introduction to Database CHAPTER 1 INTRODUCTION Database-System Applications Purpose of Database Systems View of Data Database Languages Relational Databases Database Design Data Storage and Querying Transaction Management Database Architecture Database Users and Administrators

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introduction to database
Introduction to Database

CHAPTER 1

INTRODUCTION

  • Database-System Applications
  • Purpose of Database Systems
  • View of Data
  • Database Languages
  • Relational Databases
  • Database Design
  • Data Storage and Querying
  • Transaction Management
  • Database Architecture
  • Database Users and Administrators
slide2

Database System: Introduction

  • Database Management System (DBMS)
    • Contains a large bodies of information
    • Collection of interrelated data (database)
    • Set of programs to access the data
  • Goal of a DBMS:
    • provides a way to store and retrieve database information that is both
      • convenient and
      • efficient.
  • Functions of DBMS: Management of Data (MOD)
    • Defining structure for storage data
    • Providing mechanisms for manipulation of data
    • Ensure safety of data (system crashes, unauthorized access, misused, …)
    • Concurrent control in multi-user environment
  • Computer Scientists: developed a lot of concepts and technique for MOD
    • concepts and technique form the focus of this book, and this course
1 1 database system applications
1.1 Database-System Applications
  • Database Applications:
    • Banking: all transactions
    • Airlines: reservations, schedules
    • Universities: registration, grades, student profile, ..
    • Sales: customers, products, purchases
    • Manufacturing: production, inventory, orders, supply chain
    • Human resources: employee records, salaries, tax deductions
  • Databases touch all aspects of our lives
1 2 purpose of database systems
1.2 Purpose of Database Systems
  • In the early days, database applications were built on top of file systems
  • Drawbacks of using file systems to store data:
    • Data redundancy and inconsistency
      • Multiple file formats, duplication of information in different files
    • Difficulty in accessing data
      • Need to write a new program to carry out each new task
    • Data isolation — multiple files and formats
    • Integrity problems
      • Integrity constraints (e.g. account balance > 0) become part of program code
      • Hard to add new constraints or change existing ones
drawbacks of using file systems cont
Drawbacks of using file systems (cont.)
  • Drawbacks of using file systems to store data: (cont.)
    • Atomicity of updates
      • Failures may leave database in an inconsistent state with partial updates carried out
      • E.g. transfer of funds from one account to another should either complete or not happen at all
    • Concurrent access by multiple users
      • Concurrent accessed needed for performance
      • Uncontrolled concurrent accesses can lead to inconsistencies
        • E.g. two people reading a balance and updating it at the same time
    • Security problems

Database systems offer solutions to all the above problems

原子性, 單一性

Solution

1 3 view of data and data abstraction
1.3 View of Data and Data Abstraction
  • Physical level: describes how a record (e.g., customer information) is stored in disk.
    • By sequential file, pointer, or hash structure, …
  • Logical level: describes data stored in database, and the relationships among the data.

typecustomer = recordname : string;street : string;city : string;

income : integer; end;

  • View level: application programs hide details of data types. Views can also hide information (e.g., income) for security purposes.
view of data 1 three levels
View of Data -1: Three Levels

An architecture for a database system

view of data 2 three levels

User A1

User A2

User B1

User B2

User B3

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

C, C++

DSL (Data Sub. Language)

e.g. SQL

3

1

2

External View

B

External View

@ # &

External

schema

A

External

schema

B

External/conceptual

mapping B

External/conceptual

mapping A

Database

management

system Dictionary

(DBMS) e.g. system

catalog

Conceptual

View

Conceptual

schema

<

DBA

Conceptual/internal

mapping

(Build and

maintain

schemas

and

mappings)

Storage

structure

definition

(Internal

schema)

...

1

2

3

100

Stored database (Internal View)

#

@

&

View of Data -2: Three Levels
1 3 2 instances and schemas

account

customer

1.3.2 Instances and Schemas
  • Schema – the logical structure of the database
    • e.g., the database consists of information about a set of customers and accounts and the relationship between them
    • Analogous to type information of a variable in a program
    • Physical schema: database design at the physical level
    • Logical schema: database design at the logical level

create tableaccount (account-numberchar(10),balanceinteger)

typecustomer = recordname : string;street : string;city : integer; end;

instances and schemas cont
Instances and Schemas (cont.)
  • Instance – the actual content of the database at a particular point in time
    • Analogous to the value of a variable
  • Physical Data Independence– the ability to modify the physical schema without changing the logical schema
    • Applications depend on the logical schema
    • In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.

Instance

Schema

create tableaccount (account-numberchar(10),balanceinteger)

view of data three levels
View of Data: Three Levels

An architecture for a database system

Physical Data Independence

1 3 3 data models
1.3.3 Data Models
  • A collection of conceptual tools for describing
    • data (entities, objects)
    • data relationships
    • data semantics
    • data consistency constraints
  • Data Models Provide:
    • A way to describe the design of a database at 3 levels
      • Physical level
      • Logical level
      • View level
category of data models
Category of Data Models
  • Category of Data Models:
    • Entity-Relationship model
    • Relational model
    • Object-oriented model
    • Semi-structured data models
      • Extensible Markup Language (XML)
    • Older models:
      • Network model and
      • Hierarchical model
1 4 database languages
1.4 Database Languages
  • Data Definition Language (DDL):
    • Specification notation for defining the database schema
    • E.g. create tableaccount (account-numberchar(10),balanceinteger)
  • Data Manipulation Language (DML)
    • To express database queries or updates
    • E.g. Selectaccount-numberfrom accountwhere balance >1000
  • SQL (Structured Query Language): a single language for both
1 4 1 data manipulation language dml
1.4.1 Data-Manipulation Language (DML)
  • Language for accessing and manipulating the data organized by the appropriate data model
    • DML also known as query language
    • For retrieval, insertion, deletion, modification (update)
  • Two classes of languages
    • Procedural DMLs – user specifies what data is required and how to get those data
      • E.g. … in C
    • Declarative DMLs (Nonprocedural DMLs) – user specifies what data is required without specifying how to get those data
      • E.g. In SQL: Selectaccount-numberfrom accountwhere balance > 700
  • SQL is the most widely used query language
1 4 2 data definition language ddl
1.4.2 Data-Definition Language (DDL)
  • Specification notation for defining the database schema
    • E.g. create tableaccount (account-numberchar(10),balanceinteger)
    • Define:
      • Attributes name
      • Data type
      • Consistency constraints (integrity constraints)
        • Domain constraints:

e.g. assets are integer type

        • Assertions: e.g. assets >= 0
        • Authorization: for different users
        • ….

create tablebranch (branch-namechar(15),branch-citychar(30),assetsinteger,primary key (branch-name),check (assets >= 0))

data dictionary and storage definition
Data Dictionary and Storage Definition
  • Data Dictionary:
    • DDL compiler generates a set of tables stored in a data dictionary
    • contains metadata (i.e., data about data)
      • Database schema
      • System tables
      • Users
    • Database system consults the Data dictionary before reading or modifying actual dada.
  • Data storage and definition language
      • To specify the storage structure and access methods(ch. 11,12)
      • Usually an extension of the data definition language
1 5 relational databases

DBMS environments

Relational DBMS

Relational

Data Model

C, PASCAL ,PL/1

assembler

machine

1.5 Relational Databases
  • Definition 1: A Relational Database is a databasethat is perceived by the users as a collection oftime-varying, normalized relations (tables).
    • Perceived by the users: the relational model apply at the view level and logical levels.
    • Time-varying: the set of tuples changes with time.
    • Normalized: contains no repeating group (only contains atomic value).
  • The relational model represents a database system at a level of abstraction that removed from the details of the underlying machine, like high-level language.
1 5 1 tables
1.5.1 Tables
  • Definition 2: A Relational Database is a database that is perceived by its users as a collection of tables (and nothing but tables).
1 5 2 data manipulation language
1.5.2 Data-Manipulation Language
  • SQL (Structured Query Language) : widely used
    • E.g. find the name of the customer with customer-id 192-83-7465selectcustomer.customer-namefromcustomerwherecustomer.customer-id = ‘192-83-7465’

customer

Output:

customer-name

Johnson

sql structured query language
SQL (Structured Query Language)
  • E.g. find the balances of all accounts held by the customer with customer-id 192-83-7465selectaccount.balancefromdepositor, accountwheredepositor.customer-id = ‘192-83-7465’anddepositor.account-number = account.account-number
1 5 3 data definition language
1.5.3 Data-Definition Language
  • SQL provides DDL to define database schema:
    • Tables
      • E.g. create tableaccount (account-numberchar(10),balanceinteger)
    • Assertions (ref. p.132)
      • E.g. create assertion balance-constraint

check account.balance >= 1000

    • integrity Constraints (ref. p.129)
referential integrity constraint

3. account

4. depositor

Referential Integrity Constraint

create table account(account-number char(10),branch-name char(15),balance integer,

primary key (account-number),

create table depositor(customer-name char(20),account-number char(10),

primary key (customer-name, account-number),

foreign key(account-number) references account,

存款帳

references

存款戶

1 5 4 data access from application programs

ODBC/JDBC

1.5.4 Data Access from Application Programs
  • Application programs generally access databases through one of
    • Language extensions to allow embedded SQL
    • Application program interface (e.g. ODBC/JDBC) which allow SQL queries to be sent to a database
    • ODBC: Open Database Connectivity for C
    • JDBC: Java Database Connectivity for Java language
1 6 database design
1.6 Database Design
  • Database Design - The process of designing the general structure of the database:
    • Logical Design
    • Physical Design
  • Logical Design –Deciding on the database schema.
    • To find a “good” collection of relation schemas.
    • Business decision– What attributes should we record in the database?
    • Computer Science decision– What relation schemas should we have and how should the attributes be distributed among the various relation schemas?
  • Physical Design –Deciding on the physical layout of the database
1 6 1 design process
1.6.1 Design Process
  • Phase I
    • Specification of user requirement (with domain experts)
  • Phase II
    • Conceptual design (ch. 6)
    • Choose a data model
    • Design tables
    • Normalization (ch. 7)
  • Phase III
    • Specification of functional requirements
  • Phase IV
    • Implementation
    • Logical-design
    • Physical-design (ch. 11, 12)
1 6 2 database design for banking
1.6.2 Database Design for Banking
  • Banking Database: consists 6 relations:
    • branch (branch-name, branch-city, assets)
    • customer (customer-name, customer-street, customer-only)
    • account (account-number, branch-name, balance)
    • loan (loan-number, branch-name, amount)
    • depositor (customer-name, account-number)
    • borrower (customer-name, loan-number)
example banking database

6. loan

3. depositor

5. account

存款帳

4. borrower

存款戶

貸款帳

貸款戶

Example: Banking Database

1. branch

2. customer

客戶(存款戶,貸款戶)

分公司

1 6 3 entity relationship model ch 6
1.6.3 Entity-Relationship Model (ch.6)
  • Example: Schema in the Entity-Relationship model

客戶

存款帳

存款帳

客戶(存款戶,貸款戶,信用卡戶)

存款戶

entity relationship model cont
Entity Relationship Model (cont.)
  • E-R model of real world
    • Entities (objects)
      • E.g. customers, accounts, bank branch
    • Relationships between entities
      • E.g. Account A-101 is held by customer Johnson
      • E.g. Relationship set depositor associates customers with accounts
  • Widely used for database design
    • Database design in E-R model usually converted to design in the Relational model (coming up next) which is used for storage and processing
    • Relational Model (ch. 2)
    • E-R model (ch. 6)
1 6 4 normalization

<e.g.> Supplier-and-Parts Database

S

SP

S# P# QTY

S1 P1 300

S1 P2 200

S1 P3 400

S1 P4 200

S1 P5 100

S1 P6 100

S2 P1 300

S2 P2 400

S3 P2 200

S4 P2 200

S4 P4 300

S4 P5 400

S# SNAME STATUS CITY

S1 Smith 20 London

S2 Jones 10 Paris

S3 Blake 30 Paris

S4 Clark 20 London

S5 Adams 30 Athens

P

P# PNAME COLOR WEIGHT CITY

P1 Nut Red 12 London

P2 Bolt Green 17 Paris

P3 Screw Blue 17 Rome

P4 Screw Red 14 London

P5 Cam Blue 12 Paris

P6 Cog Red 19 London

1.6.4 Normalization
  • Definition: A Relational Database is a database that is perceived by its users as a collection of tables (and nothing but tables).
problem of normalization

SP'

S'

P

P# ... ... ...

. . . .

. . . .

S1, Smith, 20, London, P1, Nut, Red, 12, London, 300

S1, Smith, 20, London, P2, Bolt, Green, 17, Paris, 200

.

.

S4, Clark, 20, London, P5, Cam, Blue, 12, Paris, 400

S# CITY P# QTY

S1 London P1 300

S1 London P2 200

. . . .

S# SNAME STATUS

S1 Smith .

S2 . .

. . .

Normalization

(異常)

Redundancy Update Anomalies!

S

P

SP

S# P# QTY

. . .

. . .

S# SNAME STATUS CITY

s1 . . London

. . . .

P# ... ... ...

. . . .

. . . .

Problem of Normalization

<e.g.>

or

1 7 object based and semistructured databases

6. borrower

1.7 Object-Based and Semistructured Databases
  • Extend the relational data model
    • by including object orientation and
    • constructs to deal with added data types. (video, image, …)
  • Allow attributes of tuples to have complex types, including
    • non-atomic values such as nested relations. (repeated data, …)
  • Preserve relational foundations,
    • in particular the declarative access to data, while extending modeling power.
1 7 2 semistructured data models
1.7.2 Semistructured Data Models
  • XML (Extensible Markup Language)
    • Defined by the WWW Consortium (W3C)
    • Originally intended as a document markup language not a database language
    • The ability to specify new tags, and to create nested tag structures made XML a great way to exchange data, not just documents
    • XML has become the basis for all new generation data interchange formats.
    • A wide variety of tools is available for parsing, browsing and querying XML documents/data

聯合

1 8 data storage and querying

Query

DBMS

Language Processor

Optimizer

Operation Processor

Access Method

File Manager

Database

1.8 Data Storage and Querying
  • Components of Database System
    • Query Processor
      • Helps to simplify to access data
      • High-level view
      • Users are not be burdened unnecessarily with the physical details
    • Storage Manager
      • Require a large amount of space
      • Can not store in main memory
      • Disk speed is slower
      • Minimize the need to move data between disk and main memory

Query Processor

Storage Manager

Goal of a DBMS: provides a way to store and retrieve data that is both convenient and efficient.

overall system structure
Overall System Structure

Overall System Structure

low-level data stored

database

1 8 1 storage management
1.8.1 Storage Management
  • Storage Manager
    • is a program module
    • that provides the interface between the low-level data stored and the application programs and queries submitted to the system.
  • Tasks of the Storage Manager:
    • interaction with the file manager (part of Operating System)
    • Translates DML into low-level file-system commands,
    • i.e. responsible for storing, retrieving and updating of data in database
  • Data Structures of the Storage Manager
    • Data files: store database itself
    • Data Dictionary: store metadata
    • Indices: provide fast access to data items that hold particular values
storage management cont
Storage Management (cont.)
  • Components of Storage manager:
    • Authorization and Integrity Manager
      • Tests for the satisfaction of integrity constraints
      • Checks the authority of users to access data
    • Transaction Manager
      • Ensure the database in a consistent state (correct) after failures
      • Ensure that concurrent transaction executions proceed without conflicting
    • File Manager
      • Manages the allocation of space on disk
      • Manages the data structures used to representation data stored
    • Buffer manager
      • Fetches data from disk into main memory
      • Decides what data to cache in main memory
1 8 2 the query processor
1.8.2 The Query Processor
  • DDL Interpreter
    • Interprets DDL statements
    • write the definitions (schema, view, ..) into the data dictionary
  • DML Compiler
    • Translates DML statements into an evaluation plan (or some evaluation plans) which consists low-level instructions
    • Query Optimization: picks the lowest cost evaluation plan
  • Query Evaluation Engine:
    • execute low-level instructions generated by the DML Compiler
flow of query processing
Flow of Query Processing

1. Parsing and translation

2. Optimization

3. Evaluation

query optimizer
Query Optimizer
  • Alternative ways of evaluating a given query
    • Equivalent expressions
    • Different algorithms for each operation
  • Cost difference between a good and a bad way of evaluating a query can be enormous
  • Need to estimate the cost of operations
    • Depends critically on statistical information about relations which the database must maintain
    • Need to estimate statistics for intermediate results to compute cost of complex expressions
example a simple query processing

DBMS

Language Processor

Internal Form :

  • ((S SP)

Optimizer

Language

Processor

Operator Processor

Access Method

Access

Method

e.g.B-tree; Index;

Hashing

File System

database

Example: A Simple Query Processing (補)

Query in SQL:

SELECT CUSTOMER. NAME

FROM CUSTOMER, INVOICE

WHERE REGION = 'N.Y.' AND

AMOUNT > 10000 AND

CUTOMER.C#=INVOICE.C

Query Processor

Operator :

SCAN C using region index, create C

SCAN I using amount index, create I

SORT C?and I?on C#

JOIN C?and I?on C#

EXTRACT name field

Calls to Access Method:

OPEN SCAN on C with region index

GET next tuple

.

.

.

Storage Manager

Calls to file system:

GET10th to 25th bytes from

block #6 of file #5

1 9 transaction management
1.9 Transaction Management
  • Transaction:
    • A transaction is a collection of operations that performs a single logical function in a database application
    • Atomicity: all or nothing
  • Failure recovery manager
    • ensures that the database remains in a consistent (correct) state,
    • Failure:
      • system failures (e.g., power failures and operating system crashes)
      • transaction failures.
  • Concurrency-control manager
    • controls the interaction among the concurrent transactions, to ensure the consistency of the database.
1 10 data mining and analysis
1.10 Data Mining and Analysis
  • Data Analysis and Mining
    • Decision Support Systems
    • Data Analysis and OLAP (Online analytical processing),
    • Data Warehousing
    • Data Mining
decision support systems
Decision-support systems

are used to make business decisions,

often based on data collected by on-line transaction systems.

Examples of business decisions:

What items to stock?

What insurance premium to change?

To whom to send advertisements?

Examples of data used for making decisions

Retail sales transaction details

Customer profiles (income, age, gender, etc.)

Decision Support Systems
data mining ch 18
Data Mining (ch.18)
  • Data mining:
    • seeks to discover knowledge automatically in the form of statistical rules and patterns from large databases. E.g. p.23: Young women buy cars.
    • is the process of semi-automatically analyzing large databases to find useful patterns
  • Prediction based on past history
    • Predict if a credit card applicant poses a good credit risk, based on some attributes (income, job type, age, ..) and past history
    • Predict if a pattern of phone calling card usage is likely to be fraudulent
  • Descriptive Patterns
    • Associations
      • Find books that are often bought by “similar” customers. If a new such customer buys one such book, suggest the others too. (library)
    • Associations may be used as a first step in detecting causation

欺騙的

引起;因果關係

1 11 database architecture
1.11 Database Architecture
  • System Structure of a Database System
    • Fig. 1.6 (p.25)
  • Application Structure
    • User uses database at the site
    • Users uses database through a network
      • Client: remote database users work
      • Sever: database system runs here
  • Partition of Database Application
    • Two-tier architecture
    • Three-tier architecture
application architectures
Application Architectures

ODBC/JDBC

  • Two-tier Architecture: e.g. client programs using ODBC/JDBC to communicate with a database
  • Three-tier Architecture: e.g. web-based applications, and applications built using “middleware”
1 12 database users and administrators

User A1

User A2

User B1

User B2

User B3

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

Host

Language

+ DSL

C, C++

DSL (Data Sub. Language)

e.g. SQL

3

1

2

External View

B

External View

@ # &

External

schema

A

External

schema

B

External/conceptual

mapping B

External/conceptual

mapping A

Database

management

system Dictionary

(DBMS) e.g. system

catalog

Conceptual

View

Conceptual

schema

<

DBA

Conceptual/internal

mapping

(Build and

maintain

schemas

and

mappings)

Storage

structure

definition

(Internal

schema)

...

1

2

3

100

Stored database (Internal View)

#

@

&

1.12 Database Users and Administrators
1 12 1 database users and user interfaces
1.12.1 Database Users and User Interfaces
  • Application programmers
    • interact with system through DML calls
  • Sophisticated users
    • Submit query without write program
    • E.g. OLAP (Online analytical processing), data mining tools
  • Specialized users
    • write specialized database applications that do not fit into the traditional data processing framework
    • E.g. CAD, expert system, complex data type (graphics, audio)
  • Naive users (end user)
    • invoke one of the permanent application programs that have been written previously
    • E.g. people accessing database over the web, bank tellers, clerical staff

複雜, 多用途

單純的

辦事員

1 12 2 database administrator
1.12.2 Database Administrator
  • Database Administrator:
    • Coordinates all the activities of the database system;
    • has a good understanding of the enterprise’s information resources and needs.
  • Database Administrator's Duties:
    • Schema definition
    • Storage structure and access method definition
    • Schema and physical organization modification
    • Granting of authorization for data access
    • Routine maintenance
      • Periodically backup database
      • Upgrade system e.g. disk
      • Monitoring performance
1 13 history of database systems
1.13 History of Database Systems
  • 1950s – early 1960:
    • Tapes: sequentially
    • Application: Payroll,
    • Input: punched decks, Output: printer
  • Late 1960s -- 1970s:
    • Disk: direct access
    • Codd proposed Relational Model, … Turing Award
  • 1980s:
    • System R: IBM Res. Lab.  IBM DB2, Oracle, Ingress, DEC Rdb
    • Replaced Network/Hierarchical model
    • Research: parallel database, distributed database, object-oriented, …
  • Early 1990s:
    • Parallel database
    • Object-Relational
  • Late 1990s:
    • World Wide Web was explosive growth
    • Database were used much more than ever before
    • Database had to support Web interfaces to data
history of database systems
History of Database Systems (補)

1995-present

1990-1995

1980-1989

1965-1979

1950-1965

Object-Oriented

OO-relation

XML

Relation

Merging data models, knowledge-base

Relation

Semantic

Object-oriented

Logic

Relation

Network

Hierarchical

Network

Hierarchical

Data Model

Relation proposed

Mainframes

Minis

PCs

Faster PCs

Workstations

Database machines

Database

Hardware

Mainframes

Mainframes

Parallel

Optical memories

WWW

Web interface

Graphics, Menus

SQL, QUEL

Query-by-forms

DL/I

COBOL+DL/I

User

Interface

Natural language

Speech input

None

Forms

Embedded

Querynon-Procedural

Integrated database

and programming

language

Program

Interface

4GL

Logic programming

Procedural

Procedural

Report

generators

Information

and transaction

processing

Business graphics

Image output

Knowledge

processing

Presentation

and display

processing

Reports

Processing

data

Reports

Processing

data

Multimedia

slide55
計算機科學的諾貝爾獎 – 杜林獎 (趙坤茂)
  • 象徵最崇高學術桂冠的諾貝爾獎,從1901年開始頒發,根據瑞典發明家諾貝爾的遺囑,設有物理、化學、生理醫學、文學及和平等五個獎項;自1969年起,增設了經濟學諾貝爾獎。
  • 疑問: 為什麼諾貝爾獎沒有數學獎項呢?坊間流傳的說法是,當初諾貝爾的夫人,曾經和瑞典一位很有成就的數學家米塔雷符勒有過一段婚外情,所以諾貝爾決定不設數學獎項。
  • 英國數學家亞蘭杜林(Alan Turing,1912-1954),雖然無緣在有生之年得到諾貝爾獎,但後人為了紀念他在數位計算理論貢獻而設立的杜林獎(Turing Award),已被公認是計算機科學領域最崇高的獎項。
  • 杜林獎從1966年開始頒發,受獎人都是對計算機科學有深遠影響的大師級學者。例如,在計算複雜度理論上有卓越貢獻的庫克(Cook)、C程式語言的創始人理奇(Ritchie)、Unix作業系統製作人湯普生(Thompson)及資料庫管理系統的先驅卡德(Codd)等。
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計算機科學的諾貝爾獎 – 杜林獎 (cont.)
  • 1936年時,杜林提出了一個假想性的計算工具,稱為杜林機器(Turing machine),這個機器有一個長條型、無窮多格的儲存磁帶,每一格位置是空白或一個符號;附帶在磁帶上的是一個可讀寫的磁頭,它可以在磁帶的格子往左或往右,並在每次移動時讀、寫或擦拭該格子;還有一個有限狀態控制機,可運用狀態的改變,配合目前磁頭所在的位置,來決定這些移動讀寫的動作。
  • 這樣一個簡單的機器,它的運算功力竟然相當於今天的數位計算機,換句話說,目前數位計算機可以運算的方法,我們都可以在杜林機器上實現!
  • 杜林也提出了如何決定電腦是否會“思考”的方法,也被視為人工智慧研究領域的基石。
  • 在二次世界大戰時,杜林曾發展一個可以破解德軍密碼的機器,不過世人在戰爭結束二十五年後才知曉。
  • 他也是馬拉松運動的好手,真是多才多藝的科學家。可惜他在1954年時就過世,只享年42歲。