Loose coupling is an approach to interconnecting the components in a system, network or software application so that those components, also called elements, depend on each other to the least extent practicable. Coupling refers to the degree of direct knowledge that one element has of another.
Loose coupling reduces the risk that a change made in one component, such as a database or user interface, creates unanticipated changes in other parts. Limiting interconnections can help isolate problems when things go wrong and simplify testing, maintenance and troubleshooting procedures.
A loosely coupled system can be easily broken down into definable modules, which are equivalent to the previously mentioned components. One way to measure the extent of coupling in a system is to map the maximum number of changes that can occur to those modules without adverse effects.
Examples of such changes include adding or removing modules or renaming, reconfiguring, rearranging or otherwise modifying them. Loosely coupled modules have less dependency on other elements and greater scalability and interoperability than with tightly coupled elements.
In object-oriented programming, dependency injections provide loosely coupled components in a program with the resources they need. Dependency injections provide code that lets the resource know which other resources it should communicate with, where to locate them and how to communicate with them.
Most organizations benefit from a loose coupling of their systems unless there is a compelling business reason to tighten their linkages. An example of a situation that requires tight coupling is a food service company, such as a restaurant, that has specific systems dealing with order processing, food supply chains, reservations, food preparation and delivery services.
Data-centric architecture often relies on loosely coupled systems because it requires a high degree of interdependence among components to ensure real-time synchronization. Web services, service-oriented architecture, event-driven architecture and microservices architecture, where different services are decoupled from each other and communicate through application programming interfaces, also make use of loose coupling.
Loose coupling generally simplifies the administration, testing, programming and maintenance activities required of a system. Each element is addressed as a separate entity with minimal concern for a trickle-down impact on other systems.
There are some distinct differences between loosely coupled and tightly coupled systems.
Tightly coupled systems have their various components linked closely to each other such that a change in one element likely affects the other elements. The overall system and its elements work together to generate an output, rather than having separate and distinct outputs from each component or element. In a tightly coupled system, changes to any one element likely affect the outputs.
In the right environment, such as a data-centric architecture or application, tight coupling might perform better than a loosely coupled architecture. Costs associated with maintaining tightly coupled architectures might be higher than with loose coupling. This is because a change in one component could require changes elsewhere in the system to maintain its overall integrity, requiring more resources and resulting in higher costs.
There is much less interaction between elements in a loosely coupled system than in a tightly coupled one. Changes to one component are unlikely to affect the others. The nodes in distributed computing systems are an example of loose coupling; they have their own memory and processing power and communicate with other nodes only when necessary.
Loosely coupled systems are often more scalable, flexible and interoperable than tightly coupled ones because changes to one part don't affect the others. This also results in lower costs much of the time.
The advantages of loose coupling include the following:
There are drawbacks as well to loose coupling, such as the following:
Learn about the basic concepts of software coupling and how to measure dependency complexity.
28 Jun 2023