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Cohesive (Or Cohesiveness)

An object is highly cohesive if it can perform a task with little or no help from other objects. Highly cohesive objects are not as dependent on other objects as objects with lower cohesion. Objects with higher cohesion are often better. Highly cohesive objects perform tasks alone and have low coupling.

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The level of interaction between objects. Lower coupling means less interaction. Lower coupling delivers better software design because objects are more independent. Lower coupling is easier to troubleshoot and update. Objects with low cohesion require lots of assistance from other objects to perform tasks and have high coupling. The manner and degree of interdependence between software modules. Types include common environment coupling, content coupling, control coupling, data coupling, hybrid coupling, and pathological coupling.
In the context of object-oriented programming, the forwarding of a request by an object to another object or delegate. An object delegates if it does not have a method to handle the message. The notation that an object can issue a request to another object in response to a request. The first object therefore delegates the responsibility to the second object. Delegation can be used as an alternative to inheritance.
The manner and degree to which the tasks performed by a single software module are related to another. Types of cohesion include coincidental, communication, functional, logical, procedural, sequential, and temporal.
Procedure to ensure that information transfers within an information system are not made from a higher security level object to an object of a lower security level.
A computation system design to perform numerous calculations simultaneously. Parallel data systems often go far beyond basic multiprocessing capabilities. They often include the concept of dividing up a large task into smaller elements and then distributing each subelement to a different processing subsystem for parallel computation. This implementation is based on the idea that some problems can be solved efficiently if they are broken into smaller tasks that can be worked on concurrently.

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