IB Computer Science 7.1.5 Centralized Vs. Distributed Control Systems Flashcards

1.1.1 Planning for a New System

1.1.2 The Importance of Change Management

1.1.3 Compatibility Challenges

1.1.4 Comparing System Implementation Approaches

1.1.5 Installation Methods and Their Evaluation

1.1.6 Data Migration Issues

1.1.7 Types of Testing

1.1.8 User Documentation and Its Importance

1.1.9 Methods of Delivering User Training

1.1.10 Causes of Data Loss

1.1.11 Managing Software Releases and Updates

1.2.1 Components of a Computer System

1.2.2 Roles of Computers in a Networked World

1.2.3 Social and Ethical Issues in a Networked World

1.2.4 Identifying Relevant Stakeholders

1.2.6 Visualizing System Requirements

1.2.7 Prototyping

1.2.8 Iteration in Design

1.2.9 End-User Involvement

1.2.10 Social and Ethical Impacts

1.2.11 Usability and Accessibility

2.1.1 CPU and Machine Instruction Cycle

2.1.2 Types of Memory

2.1.3 Functions of an Operating System

2.1.4 Features of Applications

2.1.5 Data Representation Terms

2.1.6 Boolean Operators

3.1.1 Types of Networks

3.1.2 Importance of Network Standards

3.1.3 Communication Layers in Networks

3.1.4 VPN Technologies

3.1.5 Speed Variations in Data Transmission

3.1.6 Data Compression in Transmission

3.1.7 Transmission Media

3.1.8 Packet Switching

3.1.9 Importance of Protocols

3.1.10 Wireless Networks

3.1.11 Network Security Methods

4.1.1 Procedures and Sub-Procedures

4.1.2 Decision-Making Situations

4.1.3 Inputs and Outputs in a Solution

4.1.4 Pre-Planning in Problem Solutions

4.1.5 Pre- and Post-Conditions

4.1.6 Exceptions in Problem Solutions

4.1.7 Understanding Concurrency

4.1.8 Abstraction

4.2.1 The Choice of Algorithms and Standard Algorithms

4.2.2 Standard Operations of Collections

4.2.3 Algorithm as a Flow Chart

4.2.4 Constructing Pseudocode

4.2.5 Efficiency of Algorithms

4.3.1 Fundamental Operations of a Computer

4.3.2 Features of a Computer Language

4.3.3 Need for Higher-Level Languages

4.3.4 Variables, Constants, and Operators

4.3.5 Algorithms with Loops and Branching

4.3.6 Characteristics of a Collection

5.1.1 Recognizing Recursive Thinking

5.1.2 Tracing Recursive Algorithms

5.1.3 Characteristics of a Two-Dimensional Array

5.1.4 Stacks

5.1.5 Queue

5.1.6 Arrays as Stacks and Queues

5.1.7 Logical Operations of Linked Lists

5.1.8 Trees

5.1.9 Static and Dynamic Data Structures

5.1.10 Suggesting Data Structures

6.1.1 Managing Key Resources

6.1.2 Evaluating System Resources

6.1.3 Multi-Access and Multi-Programming Environments

6.1.4 Resource Management Techniques

6.1.5 Benefits of Dedicated Operating Systems

6.1.6 The Role of a Virtual Machine

7.1.1 Types of Control Systems

7.1.2 Real-World Examples of Control System

7.1.3 Input Devices for Data Collection

7.1.4 Ethical and Social Impacts of Control Systems

7.1.6 Role of Autonomous Agents

A.1.1 Data vs. Information

A.1.2 Transactions and Data Consistency

A.2.1 DBMS and RDBMS

A.2.2 The Term Schema

A.2.3 Data Dictionary

A.2.4 Data Definition Language (DDL)

A.2.5 Data Modelling in Database Design

A.2.6 Database Terms

A.2.7 Relationships in Databases

A.2.8 Redundant Data

A.2.9 Referential Integrity

A.2.10 Normalization Forms

A.2.11 Evaluating Data Types

A.2.12 Entity-Relationship Diagrams (ERDs)

A.2.13 Designing Relational Databases

A.2.14 Queries and Views

A.2.15 Simple and Complex Queries

A.2.16 Methods to Construct a Query

A.3.1 Role of a Database Administrator

A.3.2 User Interaction with Databases

A.3.3 Methods of Data Recovery

A.3.4 Integrated Database Systems

A.3.5 Use of Databases in Various Fields

A.3.6 Privacy of Personal Data

A.3.7 Openness of Databases to Interrogation

A.3.8 Data Matching vs. Data Mining

A.4.1 Characteristics of Different Database Models

A.4.2 Object-Oriented vs. Relational Databases

A.4.3 Definition of Data Warehousing

A.4.4 Advantages of Data Warehousing

A.4.5 ETL Processes in Data Warehousing

A.4.6 Discovering Patterns with Data Mining

A.4.7 Situations Benefiting from Data Mining

A.4.8 Predictive Modeling in Data Mining

A.4.9 Database Segmentation

A.4.10 Link Analysis in Databases

A.4.11 Deviation Detection in Databases

B.1.1 Definition of Computer Modelling

B.1.2 Variables in Modelling

B.1.3 Limitations of Mathematical Models

B.1.4 Sensible Grouping for Data Items

B.1.5 Designing Test Cases

B.1.6 Effectiveness of Test Cases

B.1.7 Correctness of a Model

B.2.1 Simulations vs. Models

B.2.2 Processing Data with Rules

B.2.3 Rules and Data Representation

B.2.4 Constructing Simple Models

B.2.5 Evaluating Simulation Test Cases

B.2.6 Simulation Requirements

B.2.7 Improving Rules and Formulas

B.2.8 Constructing Complex Simulations

B.2.9 Data Collection Changes

B.2.10 Evaluating Simulation Reliability

B.2.11 Advantages and Disadvantages of Simulation

B.2.12 Ethical and Social Considerations in Predictions

B.3.1 Visualization

B.3.2 Memory Needs of 2D Visualization

B.3.3 Three-Dimensional Visualization

B.3.4 Memory and 3D Visualization

B.3.5 Time and Memory Considerations in 3D Animation

B.4.1 Genetic Algorithms

B.4.2 Structure of Neural Networks

B.4.3 Applications of Neural Network Modelling

B.4.4 Neural Networks for Pattern Recognition

B.4.5 Structures of Natural Language

B.4.6 Human vs. Machine Language

B.4.7 Evolution of Machine Translators

B.4.8 Chatbots and Conversation Simulation

B.4.9 Advances in Natural Language Processing

C.1.1 Internet vs. World Wide Web

C.1.2 Evolution of the Web

C.1.3 Characteristics of Web Technologies

C.1.4 Uniform Resource Identifier and URL

C.1.5 Purpose of a URL

C.1.6 Domain Name Server

C.1.7 Internet Protocols

C.1.8 Components of a Web Page

C.1.9 Protocols and Standards on the Web

C.1.10 Types of Web Pages

C.1.11 Static vs. Dynamic Web Pages

C.1.12 Functions of a Browser

C.1.13 Client-Side vs. Server-Side Scripting

C.1.14 Web Pages and Data Sources

C.1.15 Common Gateway Interface (CGI)

C.1.16 Web Page Structure

C.2.1 Search Engines

C.2.2 Principles of Search Algorithms

C.2.3 How Web Crawlers Function

C.2.4 Metadata and Web Crawlers

C.2.5 Parallel Web Crawling

C.2.6 Web-Indexing in Search Engines

C.2.7 Improving Search Results

C.2.8 Metrics Used by Search Engines

C.2.9 Search Engine Effectiveness

C.2.10 White Hat and Black Hat SEO

C.2.11 Challenges for Growing Search Engines

C.3.1 Mobile and Distributed Computing

C.3.2 Interoperability and Open Standards

C.3.3 Hardware for Distributed Networks

C.3.4 Role of Distributed Systems in Web Growth

C.3.5 Lossless vs. Lossy Compression

C.3.6 Effectiveness of Compression Software

C.4.1 Growth of Online Interaction

C.4.2 Cloud Computing Architecture

C.4.3 Effects of Cloud Computing

C.4.4 Copyright and Intellectual Property

C.4.5 Privacy and Authentication

C.4.6 Future of Web Infrastructure

C.4.7 Web Monopolies

C.4.8 Decentralized and Democratic Web

C.5.1 Web as a Directed Graph

C.5.2 Web Graph vs. Sub-Graphs

C.5.3 Web Graph Features

C.5.4 Role of Graph Theory in Web Connectivity

C.5.5 Page Rank Algorithm

C.5.6 Power Laws and Web Development

C.6.1 Semantic Web vs .Text-Web vs. Multimedia-Web

C.6.2 Aims of the Semantic Web

C.6.3 Ontology vs. Folksonomy

C.6.4 Folksonomies and Social Structures

C.6.5 Expressivity and Usability in Semantic Web

C.6.6 Searching Methods for Semantic Web

C.6.7 Ambient Intelligence vs. Collective Intelligence

C.6.8 Ambient Intelligence for Support

C.6.9 Collective Intelligence for Complex Issues

D.1.1 Nature of an Object

D.1.2 Unified Modeling Language (UML)

D.1.3 Decomposition of a Problem

D.1.4 Relationships Between Objects

D.1.5 Data Types for Representing Data

D.1.6 Passing Data to and from Actions

D.2.1 Encapsulation

D.2.2 Inheritance

D.2.3 Polymorphism

D.2.4 Libraries of Objects

D.2.5 Disadvantages of OOP

D.2.6 Modularity

D.3.1 Key Terminologies

D.3.2 Object Methods and Access

D.3.3 Selection Statements

D.3.4 Repetition Statements

D.3.5 Static Arrays

D.3.6 Internationalization Features

D.3.7 Ethical and Moral Obligations

D.4.1 Understanding Recursion

D.4.2 Tracing Recursive Algorithms

D.4.3 Object References

D.4.4 Abstract Data Type (ADT) List

D.4.5 Applications of Lists

D.4.6 Static List Implementations

D.4.7 Linked List Algorithms with Object References

D.4.8 Standard Library Collections

D.4.9 Tracing List Implementations

D.4.10 ADT Stack, Queue, and Binary Tree Features

D.4.11 Importance of Style and Naming Conventions