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In parallel computing, granularity (or grain size) of a task is a measure of the amount of work (or computation) which is performed by that task. [1]Another definition of granularity takes into account the communication overhead between multiple processors or processing elements.
In software engineering, "programming in the large" and "programming in the small" refer to two different aspects of writing software. "Programming in the large" means designing a larger system as a composition of smaller parts, and "programming in the small" means creating those smaller parts by writing lines of code in a programming language.
In software engineering, coupling is the degree of interdependence between software modules, a measure of how closely connected two routines or modules are, [1] and the strength of the relationships between modules. [2] Coupling is not binary but multi-dimensional. [3] Coupling and cohesion. Coupling is usually contrasted with cohesion.
In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality : how well a range of different problems can be expressed for a variety of different architectures ...
Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model . A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
Software testing can provide objective, independent information about the quality of software and the risk of its failure to a user or sponsor. [1] Software testing can determine the correctness of software for specific scenarios but cannot determine correctness for all scenarios. [2] [3] It cannot find all bugs.
This led to the design of parallel hardware and software, as well as high performance computing. [ 8 ] Frequency scaling was the dominant reason for improvements in computer performance from the mid-1980s until 2004.
Some of these models of concurrency are primarily intended to support reasoning and specification, while others can be used through the entire development cycle, including design, implementation, proof, testing and simulation of concurrent systems. Some of these are based on message passing, while others have different mechanisms for concurrency.