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Coupling and cohesion. Coupling is usually contrasted with cohesion. Low coupling often correlates with high cohesion, and vice versa. Low coupling is often thought to be a sign of a well-structured computer system and a good design, and when combined with high cohesion, supports the general goals of high readability and maintainability ...
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 ...
High cohesion is an evaluative pattern that attempts to keep objects appropriately focused, manageable and understandable. High cohesion is generally used in support of low coupling. High cohesion means that the responsibilities of a given set of elements are strongly related and highly focused on a rather specific topic.
They aid in understanding which classes should go into which packages (package cohesion) and how these packages should relate with one another (package coupling). Package principles also includes software package metrics , which help to quantify the dependency structure, giving different and/or more precise insights into the overall structure ...
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]
Cohesion which is "concerned with the grouping of functionally related processes into a particular module", [12] and; Coupling relates to "the flow of information or parameters passed between modules. Optimal coupling reduces the interfaces of modules and the resulting complexity of the software". [12]
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Common types of connascence include connascence of name, type, position, and meaning. Certain coupling types naturally align with specific connascence types; for example, data coupling often involves connascence of name or type. However, not every combination of coupling and connascence is practically meaningful.