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This A-to-Z glossary defines key Computer Science terms you need to know. Computer science professionals pursue a career focused on various aspects of computing technology and its applications. They possess a diverse skill set encompassing computer programming, algorithms, data structures, software development, database management, computer ...
Each term and definition show its connection to one or more of the computer science concepts as indicated on the left of the table: Foundational Concepts (FC); Algorithmic Thinking (AT); Programming Concepts (PC); Data & Analysis (DA), Networking & the Internet (NI); and Impacts of Computing (IC).
This glossary of computer science is a list of definitions of terms and concepts used in computer science, its sub-disciplines, and related fields, including terms relevant to software, data science, and computer programming
- Overview
- Big idea 1: Creative development
- Big idea 2: Data
- Big idea 3: Algorithms and programming
- Big idea 4: Computer systems and networks
- Big idea 5: Impact of computing
The AP Computer Science Principles exam introduces a wide range of topics across the field of computer science.
This review highlights terminology from the big ideas that are new to most students and includes links to more in-depth explanations.
Big idea 1: Creative development
syntax error: A mistake in typed code that violates the rules of the programming language. Typically, code with syntax errors will not run.
logic error: A mistake in an algorithm or program that causes it to behave unexpectedly or return the incorrect value.
run-time error: A mistake in a program that happens only when the program is actually run, such as a program attempting to access memory that does not exist.
syntax error: A mistake in typed code that violates the rules of the programming language. Typically, code with syntax errors will not run.
logic error: A mistake in an algorithm or program that causes it to behave unexpectedly or return the incorrect value.
run-time error: A mistake in a program that happens only when the program is actually run, such as a program attempting to access memory that does not exist.
overflow error: Error that results when the number of bits is not enough to represent the number (like a car’s odometer “rolling over”). Learn more in Number limits, overflow, and round-off.
bit: A binary digit, either 0 or 1. Learn more in Binary numbers.
byte: A sequence of 8 bits. Learn more in Bytes.
roundoff: Error that results when the number of bits is not enough to represent the number with full precision (like using 3 digits to represent π as 3.14). Learn more in Number limits, overflow, and roundoff.
analog data: Values that change smoothly, rather than in discrete intervals, over time. For example, the pitch and volume of a live concert. Learn more in From analog to digital data.
lossless: Compressing data in a way that preserves all data away and allows full recovery of the original. Learn more in Data compression.
lossy: Compressing data in a way that discards some data and makes it impossible to recover the original. Learn more in Data compression.
sequencing: The sequential execution of steps in an algorithm or code in a program (like steps in a recipe). Learn more in The building blocks of algorithms.
selection: A Boolean condition to determine which of two paths are taken in an algorithm or program. Learn more in The building blocks of algorithms and Conditionals: if, else, and Booleans.
iteration: The repetition of steps in an algorithm or program for a certain amount of times or until a certain condition is met. Learn more in The building blocks of algorithms and Repetition.
linear search : An algorithm that iterates through each item in a list until it finds the target value. Learn more in Measuring an algorithm's efficiency.
binary search: An algorithm that searches a sorted list for a value by repeatedly splitting the list in half. Learn more in Measuring an algorithm's efficiency.
reasonable time: A run time for an algorithm that doesn't increase faster than a polynomial function of the input size (like 10n , n2 , etc). An unreasonable run time would increase superpolynomially (like 2n or n! ). Learn more in Categorizing run time efficiency.
computing device: A physical device that can run a program, such as a computer, smart phone, or smart sensor.
computer network: A group of interconnected computing devices capable of sending or receiving data. Learn more in Computer networks.
bandwidth: The maximum amount of data that can be sent in a fixed period of time over a network connection, typically measured in bits per second. Learn more in Bit rate, bandwidth, and latency.
protocol: An agreed upon set of rules that specify the behavior of a system. Learn more in Open protocol development.
scalability: The ability of a system to adjust in scale to meet new demands. Learn more in Scalable systems.
IP (Internet Protocol): The protocol that determines how to address nodes on the network (with IP addresses) and how to route data from one node to a destination node (using routers). Learn more in IP addresses and Routing with redundancy.
digital divide: The idea that some communities or populations have less access to computing than others, typically due to limitations of Internet speed or computer hardware access. Learn more in The digital divide
crowdsourcing: A model in which many online users combine efforts to help fund projects, generate ideas, or create goods or services (like Wikipedia). Learn more in Crowdsourcing innovations.
citizen science: Crowdsourcing for science! The participation of volunteers from the public in a scientific research project (like collecting rain samples or counting butterflies). Learn more in Citizen science.
Creative Commons: An alternative to copyright that allows people to declare how they want their artistic creations to be shared, remixed, used in noncommercial contexts, and how the policy should propagate with remixed versions. Learn more in Creative commons and open source.
open access: A policy that allows people to have access to documents (like research papers) for reading or data (like government datasets) for analysis. Learn more in Sharing science research online.
PII (Personally identifiable information): Information about an individual that can be used to uniquely identify them (directly or indirectly). Learn more in PII (Personally identifiable information).
Learn the basic information technology (IT) terminology. From 4G to zero trust, expand your vocabulary with our list of terms beginners need to know.
Dec 27, 2022 · Learning some of the most commonly used computer science terms can help you strengthen your skills and communicate confidently with others in the industry. In this article, we define 28 computer science terms and explain why it's helpful to learn them.
Here is a very simple glossary of computer science terms. It covers hardware, software, and related ideas. In some cases a narrow de nition is given for simplicity sake. This makes a good glossary for an introduction to computer science. You should also check out the number systems handout. 256 - This is 2 to the 8th power.
