Big Idea 4 — Computer Systems and Networks
How the Internet moves data, why it keeps working when parts fail, and how parallel and distributed computing solve problems faster. This Big Idea is worth 11–15% of the AP exam. Each section ends with a short practice set — click "Show answer" to check yourself.
Big Idea 3 — Algorithms and Programming
The heart of AP CSP: variables, lists, conditionals, loops, procedures, libraries, simulations, algorithm efficiency, and the limits of computing. This Big Idea is worth 30–35% of the AP exam and supports the Create Performance Task. Code uses AP exam pseudocode (lists start at index 1). Each section ends with a short practice set — click "Show answer" to check yourself.
Big Idea 2 — Data
How computers represent data with bits, how data is shrunk for storage and transmission, and how people and programs turn raw data into useful information. This Big Idea is worth 17–22% of the AP exam. Each section ends with a short practice set — click "Show answer" to check yourself.
Big Idea 1 — Creative Development
How computing innovations are made: working with others, understanding what a program does and why, following a design process, and finding and fixing mistakes. This Big Idea is worth 10–13% of the AP exam and also underpins the Create Performance Task. Each section ends with a short practice set — click "Show answer" to check yourself.
The Internet
A computing device is a machine that can run a program (computer, tablet, phone, smart sensor). A computer network is a group of connected devices that can send and receive data. The Internet is a network of networks that connects billions of devices worldwide.
- A path is the sequence of connected devices that data travels from a sender to a receiver.
- Routers pass data along the path toward its destination. There is no single central controller of the Internet.
- A protocol is an agreed-upon set of rules that devices follow to communicate. The Internet is built on open protocols that anyone can use, which allows it to grow easily (it is scalable).
- An IP address is a unique number identifying a device on the network. DNS (Domain Name System) translates names like
example.cominto IP addresses.
Packets
- Data sent over the Internet is split into small packets. Each packet carries part of the data plus metadata (such as the destination and the packet's order).
- Packets can take different routes and may arrive out of order; the receiver reassembles them.
- TCP handles reliable delivery: it checks for missing packets, asks for them again, and puts them in order. IP handles addressing and routing.
| Term | Meaning |
|---|---|
| Bandwidth | Maximum amount of data that can be sent in a fixed time (e.g. bits per second) |
| Latency | The time it takes for data to travel from sender to receiver |
The World Wide Web is a system of linked pages and files that runs on the Internet (using the HTTP protocol). The Web and the Internet are not the same thing.
1. Why is data split into packets before being sent?
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2. A video call has slow response even though the connection transfers lots of data per second. Is the problem bandwidth or latency?
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3. What does DNS do?
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4. Is the World Wide Web the same as the Internet?
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Fault Tolerance
A system is fault-tolerant if it can keep working even when some of its components fail. This is achieved through redundancy — having backup paths or parts.
- The Internet is fault-tolerant because there are multiple possible paths between any two devices. If a router or cable fails, packets are rerouted along another path.
- Routing is dynamic: no one fixed path is required, so the network adapts to failures and heavy traffic.
- More redundancy makes a network more reliable, but adds cost (extra cables, routers, and equipment).
- Fault tolerance helps the Internet scale and stay available.
A ─── B ─── D \ / └─── C ──────┘ // Two paths from A to D: A–B–D and A–C–D. // If B fails, data can still reach D through C.
1. What is redundancy, and how does it help a network?
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2. In the diagram above, can A still reach D if C fails?
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3. Give one drawback of adding more redundancy.
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Parallel and Distributed Computing
Computing can be organized in three ways:
| Model | How it works |
|---|---|
| Sequential | Operations run one at a time, in order |
| Parallel | The program is split into parts, and some parts run at the same time on multiple processors or cores in one machine |
| Distributed | Multiple separate devices work together on a problem, communicating over a network |
- Parallel and distributed computing can solve larger problems and finish faster than a single sequential processor.
- Distributed systems can use resources from many machines and scale up — examples include cloud computing and volunteer projects that analyze science data.
- Speedup = (time to run sequentially) ÷ (time to run in parallel).
- A parallel program's time = the sequential portion + the longest parallel portion.
- Limits: some steps must be done in order, and splitting work and combining results adds overhead, so adding processors doesn't speed things up forever.
Process A: 40 seconds Process B: 60 seconds (independent) Sequential : 40 + 60 = 100 seconds Parallel : both run at once → longest = 60 seconds Speedup : 100 ÷ 60 ≈ 1.67
1. Tasks of 30 s and 50 s are independent. How long do they take in parallel on two processors?
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2. A job takes 120 s sequentially and 40 s in parallel. What is the speedup?
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3. What is the difference between parallel and distributed computing?
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4. Why can't you always speed up a program by adding more processors?