Computer Science

An abstract data type (ADT) is a model for data structures that defines operations without specifying implementation details.

Algorithmic probability quantifies the likelihood of a string appearing based on its shortest description.

Analysis of algorithms studies the efficiency and performance of algorithms using mathematical techniques.

An anytime algorithm is a type of algorithm that can provide a solution at any time, improving its result with more computation.

Approximate string matching is a technique for finding similar strings within a dataset, allowing for errors or variations.

Artificial Intelligence (AI) refers to computer systems designed to perform tasks that typically require human intelligence.

Asymptotic computational complexity measures an algorithm's efficiency as input size grows, focusing on growth rates rather than specific performance.

Automata Theory is the study of abstract machines and the problems they can solve.

Automated reasoning is the use of algorithms to derive conclusions from premises using formal logic.

The Bellman Equation is a fundamental recursive relationship in dynamic programming used to solve optimization problems.

Bitwise operations are mathematical operations that directly manipulate bits of binary numbers.

The Boolean satisfiability problem (SAT) asks if there is a way to assign true/false values to variables to satisfy a logical formula.

Cache eviction is the process of removing stored data from a cache when it is full or when data is no longer needed.

Combinatorial optimization involves finding the best solution from a finite set of possible solutions.

A Command Line Interface (CLI) is a text-based interface used to interact with software and operating systems.

Computational complexity theory studies the resources needed for algorithms to solve problems.

Computational Creativity is the use of algorithms and AI to simulate human-like creative processes.

Computational Learning Theory studies the algorithms and models that enable computers to learn from data.

Computational linguistics is the study of using computer algorithms to process and analyze human language.

Computational mathematics is the study of algorithms and numerical methods for solving mathematical problems using computers.

Computational neuroscience is the study of brain function through mathematical models and computer simulations.

Computational number theory is the study of algorithms for solving problems in number theory using computational techniques.

Computational statistics involves using computer algorithms to analyze and interpret statistical data.

Decomposition is the process of breaking down complex problems into simpler, more manageable parts.

Discrete Mathematics is the study of mathematical structures that are fundamentally discrete rather than continuous.

Disjunctive Normal Form (DNF) is a way to express logical formulas using ORs and ANDs.

A dynamic graph is a graph that changes over time, allowing for the addition or removal of nodes and edges.

Dynamic Programming is a method for solving complex problems by breaking them down into simpler subproblems.