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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.
Cohesion is often contrasted with coupling. High cohesion often correlates with loose coupling, and vice versa. [2] The software metrics of coupling and cohesion were invented by Larry Constantine in the late 1960s as part of Structured Design, based on characteristics of “good” programming practices that reduced maintenance and ...
The model is named after database pioneer Charles Bachman, and mostly used in computer software design. In a relational model, a relation is the cohesion of attributes that are fully and not transitive functional dependent [clarify] of every key in that relation. The coupling between the relations is based on accordant attributes.
Four types of autonomy, which promote loose coupling, are: reference autonomy, time autonomy, format autonomy, and platform autonomy. [3] Loose coupling is an architectural principle and design goal in service-oriented architectures. Eleven forms of loose coupling and their tight coupling counterparts are listed in: [4]
For example, an attribute associated with portability is the number of target-dependent statements in a program. More precisely, using the Quality Function Deployment approach, these measurable attributes are the "hows" that need to be enforced to enable the "whats" in the Software Quality definition above.
The indirection pattern supports low coupling and reuses potential between two elements by assigning the responsibility of mediation between them to an intermediate object. An example of this is the introduction of a controller component for mediation between data (model) and its representation (view) in the model-view-controller pattern.
Coupling describes the degree and nature of dependency between software components, focusing on what they share (e.g., data, control flow, technology) and how tightly they are bound. It evaluates two key dimensions: strength, which measures how difficult it is to change the dependency, and scope (or visibility), which indicates how widely the ...
Architectural and structural complexity are an area of research in systems theory to measure the cohesion and coupling and is based on the metrics commonly used in software development projects. Zeigler, Kim, and Praehofer present a theory of modeling and simulation which provides a conceptual framework and an associated computational approach ...