Client–server modelThe client–server model is a distributed application structure that partitions tasks or workloads between the providers of a resource or service, called servers, and service requesters, called clients. Often clients and servers communicate over a computer network on separate hardware, but both client and server may reside in the same system. A server host runs one or more server programs, which share their resources with clients. A client usually does not share any of its resources, but it requests content or service from a server.
Thin clientIn computer networking, a thin client is a simple (low-performance) computer that has been optimized for establishing a remote connection with a server-based computing environment. They are sometimes known as network computers, or in their simplest form as zero clients. The server does most of the work, which can include launching software programs, performing calculations, and storing data.
Rich clientIn computer networking, a rich client (also called heavy, fat or thick client) is a computer (a "client" in client–server network architecture) that typically provides rich functionality independent of the central server. This kind of computer was originally known as just a "client" or "thick client," in contrast with "thin client", which describes a computer heavily dependent on a server's applications. A rich client may be described as having a rich user interaction.
Client (computing)In computing, a client is a piece of computer hardware or software that accesses a service made available by a server as part of the client–server model of computer networks. The server is often (but not always) on another computer system, in which case the client accesses the service by way of a network. A client is a computer or a program that, as part of its operation, relies on sending a request to another program or a computer hardware or software that accesses a service made available by a server (which may or may not be located on another computer).
Reduction (complexity)In computability theory and computational complexity theory, a reduction is an algorithm for transforming one problem into another problem. A sufficiently efficient reduction from one problem to another may be used to show that the second problem is at least as difficult as the first. Intuitively, problem A is reducible to problem B, if an algorithm for solving problem B efficiently (if it existed) could also be used as a subroutine to solve problem A efficiently. When this is true, solving A cannot be harder than solving B.
Email clientAn email client, email reader or, more formally, message user agent (MUA) or mail user agent is a computer program used to access and manage a user's email. A web application which provides message management, composition, and reception functions may act as a web email client, and a piece of computer hardware or software whose primary or most visible role is to work as an email client may also use the term. Like most client programs, an email client is only active when a user runs it.
Complexity classIn computational complexity theory, a complexity class is a set of computational problems "of related resource-based complexity". The two most commonly analyzed resources are time and memory. In general, a complexity class is defined in terms of a type of computational problem, a model of computation, and a bounded resource like time or memory. In particular, most complexity classes consist of decision problems that are solvable with a Turing machine, and are differentiated by their time or space (memory) requirements.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Parameterized complexityIn computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output. The complexity of a problem is then measured as a function of those parameters. This allows the classification of NP-hard problems on a finer scale than in the classical setting, where the complexity of a problem is only measured as a function of the number of bits in the input.
