Separation of concerns

In

Separation of concerns results in more degrees of freedom for some aspect of the program's design, deployment, or usage. Common among these is increased freedom for simplification and maintenance of code. When concerns are well-separated, there are more opportunities for module upgrade, reuse, and independent development. Hiding the implementation details of modules behind an interface enables improving or modifying a single concern's section of code without having to know the details of other sections and without having to make corresponding changes to those other sections. Modules can also expose different versions of an interface, which increases the freedom to upgrade a complex system in piecemeal fashion without interim loss of functionality.^[citation needed]

Separation of concerns is a form of abstraction. As with most abstractions, separating concerns means adding additional code interfaces, generally creating more code to be executed. The extra code can result in higher computation costs in some cases, but in other cases also can lead to reuse of more optimized code. So despite the many benefits of well-separated concerns, there may be an associated execution penalty.^{[citation needed]}

The mechanisms for modular or object-oriented programming that are provided by a

Separation of concerns is an important design principle in many other areas as well, such as urban planning, architecture and information design.^[5] The goal is to more effectively understand, design, and manage complex interdependent systems, so that functions can be reused, optimized independently of other functions, and insulated from the potential failure of other functions.

Common examples include separating a space into rooms, so that activity in one room does not affect people in other rooms, and keeping the stove on one circuit and the lights on another, so that overload by the stove does not turn the lights off. The example with rooms shows encapsulation, where information inside one room, such as how messy it is, is not available to the other rooms, except through the interface, which is the door. The example with circuits demonstrates that activity inside one module, which is a circuit with consumers of electricity attached, does not affect activity in a different module, so each module is not concerned with what happens in the other.

The term separation of concerns was probably coined by Edsger W. Dijkstra in his 1974 paper "On the role of scientific thought".^[6]

Let me try to explain to you, what to my taste is characteristic for all intelligent thinking. It is, that one is willing to study in depth an aspect of one's subject matter in isolation for the sake of its own consistency, all the time knowing that one is occupying oneself only with one of the aspects. We know that a program must be correct and we can study it from that viewpoint only; we also know that it should be efficient and we can study its efficiency on another day, so to speak. In another mood we may ask ourselves whether, and if so: why, the program is desirable. But nothing is gained—on the contrary!—by tackling these various aspects simultaneously. It is what I sometimes have called "the separation of concerns", which, even if not perfectly possible, is yet the only available technique for effective ordering of one's thoughts, that I know of. This is what I mean by "focusing one's attention upon some aspect": it does not mean ignoring the other aspects, it is just doing justice to the fact that from this aspect's point of view, the other is irrelevant. It is being one- and multiple-track minded simultaneously.

Fifteen years later, it was evident the term separation of concerns was becoming an accepted idea. In 1989, Chris Reade wrote a book titled Elements of Functional Programming^[7] that describes separation of concerns:

The programmer is having to do several things at the same time, namely,

1. describe what is to be computed;
2. organise the computation sequencing into small steps;
3. organise memory management during the computation.

Reade continues to say,

Ideally, the programmer should be able to concentrate on the first of the three tasks (describing what is to be computed) without being distracted by the other two, more administrative, tasks. Clearly, administration is important, but by separating it from the main task we are likely to get more reliable results and we can ease the programming problem by automating much of the administration.

The separation of concerns has other advantages as well. For example, program proving becomes much more feasible when details of sequencing and memory management are absent from the program. Furthermore, descriptions of what is to be computed should be free of such detailed step-by-step descriptions of how to do it, if they are to be evaluated with different machine architectures. Sequences of small changes to a data object held in a store may be an inappropriate description of how to compute something when a highly parallel machine is being used with thousands of processors distributed throughout the machine and local rather than global storage facilities.

Automating the administrative aspects means that the language implementor has to deal with them, but he/she has far more opportunity to make use of very different computation mechanisms with different machine architectures.

Separation of concerns is crucial to the design of the Internet. In the

Subject-oriented programming allows separate concerns to be addressed as separate software constructs, each on an equal footing with the others. Each concern provides its own class-structure into which the objects in common are organized, and contributes state and methods to the composite result where they cut across one another. Correspondence rules describe how the classes and methods in the various concerns are related to each other at points where they interact, allowing composite behavior for a method to be derived from several concerns. Multi-dimensional separation of concerns allows the analysis and composition of concerns to be manipulated as a multi-dimensional "matrix" in which each concern provides a dimension in which different points of choice are enumerated, with the cells of the matrix occupied by the appropriate software artifacts.

In cognitive science and artificial intelligence, it is common to refer to David Marr's levels of analysis. At any given time, a researcher may be focusing on (1) what some aspect of intelligence needs to compute, (2) what algorithm it employs, or (3) how that algorithm is implemented in hardware. This separation of concerns is similar to the interface/implementation distinction in software and hardware engineering.

In normalized systems separation of concerns is one of the four guiding principles. Adhering to this principle is one of the tools that helps reduce the combinatorial effects that, over time, get introduced in software that is being maintained. In normalized systems separation of concerns is actively supported by the tools.

Separation of concerns can be implemented and enforced via

class Bear
  def hunt
    forest.select(&:food?)
  end
end

class Bear
  def eat(food)
    raise "#{food} is not edible!" unless food.respond_to? :nutrition_value
    food.nutrition_value
  end
end

class Bear
  attr_accessor :hunger
  def monitor_hunger
    if hunger > 50
      food = hunt
      hunger -= eat(food)
    end
  end
end