Name: 🌶️ AP Comp Sci P Cram Review: Big Idea 4: Computer Systems and Networks
Uploaded: 2021-04-04T22:00:00.000Z
Description: Big Idea 4: Computer Systems and Networks

AP Computer Science Principles

Check out what the first big idea of AP Computer Science A is: creative development. These resources cover program functions, program design, and the correct process for identifying and then correcting errors. These resources will make sure you fully understand program development for this course!

Unit 1 – Creative Development

The second big idea of AP Computer Science A is data! These resources will show the importance of data, data compression, how to identify information within forms of data, and how to effectively use programs in combination with data. It also covers lossy data and data compression explanations and examples.

Unit 2 – Data

Learn all you need to know about the third big idea of AP Computer Science A: algorithms and programming. This covers variables, effective algorithms, mathematical expressions, boolean expressions, developing algorithms, and much more. This will make sure you understand the importance of algorithms and programming within the course!

Unit 3 – Algorithms & Programming

The fourth big idea of AP Computer Science A is all about computer systems and networks. These resources cover an overview of the internet, fault tolerance, and a comparison of parallel and distributed computing. This will make it easier to fully understand the importance of this big idea!

Unit 4 – Computer Systems & Networks

Finally, the last big idea of AP Computer Science A: the impact of computing. We cover the positive and negative impacts of computing, computing bias, crowdsourcing, the digital divide and so much more so you can fully understand the wide reaching consequences both legally and morally and how to complete safe computing.

Unit 5 – Impact of Computing

Frequently Asked Questions

Check out these resources that provide helpful advice and information in order to prepare you for your AP Computer Science P exam. With explanations about the multiple choice section, performance tasks, and a complete exam guide, these resources will make sure you are completely prepared to take and ace your exam!

Previous Exam Prep

AP Cram Sessions 2021

First Unit

Study Tools

Exam Skills

Developing an Understanding

Building Computational Thinking Practices

The AP Exam

Summary of Upcoming Topics:

Big Idea 1 Overview: Creative Development

Computing Innovations

Examples of Computing Innovations:

Collaboration in Computer Science

Collaboration Between Users and Developers

Computing Developments that Foster Collaboration

Ways to be a Good Team Player!

Intro to Big Idea 1: Creative Development and Collaboration

Computing Innovations and Their Purposes

Concepts to Know

Programs and Code Segments... with Cake

Describing Programs

Program Inputs

Types of Inputs

Program Outputs

Types of Outputs

Program Events

Examples of Common Events:

Event-Driven Software

Program Behavior

Program Function and Purpose

Types of Development Processes

Iterative and Incremental Development Processes

The Drawing Board: Phases of Program Development

Investigation and Reflection

Designing Code

Program Requirements and Specifications

Program Documentation

Comments

Sourcing Your Work

Program Design and Development

Common Errors

Error Fixes

Testing 

Testing Challenges 

Good Testing Practices

Error-Hunting Example

Whew!

Identifying and Correcting Errors

The One Thing You Need to Know About this Big Idea:

2.1 Binary Numbers

Key Ideas

Vocabulary

Resources

2.2 Data Compression

2.3 Extracting Information from Data

2.4 Using Programs with Data

Exam Weighing

Number Bases

Bit Representations

Abstraction

Analog Data and Bit Representations

Overflow Errors

Binary Numbers

Data Compression Examples

Lossless vs. Lossy Data Compression

Lossless Data Compression

Lossy Data Compression

Data Compression

Metadata

Problems Collecting and Processing Data

Data Biases

Extracting Information from Data

Transforming Data

Data Analysis Discoveries

In conclusion...

Using Programs with Data

The One Thing You Need to Know About This Big Idea:

3.1 Variables and Assignments

3.2 Data Abstraction

3.3 Mathematical Expressions

3.4 Strings

3.5 Boolean Expressions

3.6 Conditionals

3.7 Nested Conditionals

3.8 Iteration 

3.9 Developing Algorithms

3.10 Lists

3.11 Binary Search

3.12 Calling Procedures

3.13 Developing Procedures

3.14 Libraries

3.15 Random Values

3.16 Simulations

3.17 Algorithmic Efficiency

3.18 Undecidable Problems

Exam Weighing:

Big Idea 3: Algorithms and Programming

Variables in Pseudocode and Python

Data Types

Variables and Assignments

Basic List Operators

Accessing an element by index

Assigning the value of an element of a list to a variable

Assigning a value to an element outright

Assigning the value of one element in the list to another

Adding and Removing Elements

Inserting elements at a given index

Adding elements to the end of the list

Removing elements

Determining the length of a list

Looping through Lists

Complete Traversal

Partial Traversal

Lists

Traversing a List

Binary Search

Parts of a Procedure:

Calling Procedures

Procedural Abstraction

Developing Procedures

API Software Libraries

Libraries

Generating Random Numbers

Random Values

Abstraction in Simulations

Simulations

Problems

Efficiency

Algorithmic Efficiency

Conclusion

Undecidable Problems

Lists in AP CSP Pseudocode

Data Abstraction

Sequencing

Expressions

Mathematical Expressions

What are Strings?

Slicing

Concatenation

Strings

Boolean Variables

Not, And, Or

Not Operator

And Operator

Or Operator

Boolean Expressions

If Statement

Else Statement

Conditionals

Nested Conditional Example

Nested Conditionals

Repeat n Times

Repeat Until (condition)

Iteration Practice Problem

More Operators in Loops

Iteration

Existing Algorithm Types

Developing Algorithms

4.1 The Internet

4.2 Fault Tolerance 

4.3 Parallel and Distributed Computing

Example Problem 

Answer

Big Idea 4 Overview: Computer Systems and Networks

Computing Devices, Systems, and Networks

Data Streams, Packets, and Routing

Bandwidth

Internet Protocols

The World Wide Web

Scalability

The Internet

What is Fault Tolerance?

Redundancy

Benefits of Fault Tolerance

Disadvantages of Fault Tolerance

Fault Tolerance

Parallel and Distributed Computing Definitions

Execution Time, Efficiency, and Speedup Calculations

Calculating Execution Time 

Sequential Solutions

Parallel Computing Solutions

Calculating the Speedup

Speed Limits

Example Problem

In Conclusion...

Parallel and Distributed Computing

5.1 Beneficial and Harmful Effects

Vocabulary 

Big Idea 5 Overview: Impact of Computing