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Top Answer
Answered Jul 27, 2020 · 274 votes
At the time of writing this, the top voted answers on this page are imprecise and muddled on the declarative vs. imperative definition, including the answer that quotes Wikipedia. Some answers are conflating the terms in different ways.
Refer also to my explanation of why spreadsheet programming is declarative, regardless that the formulas mutate the cells.
Also, several answers claim that functional programming must be a subset of declarative. On that point it depends if we differentiate "function" from "procedure". Lets handle imperative vs. declarative first.
Definition of declarative expression
The only attribute that can possibly differentiate a declarative expression from an imperative expression is the referential transparency (RT) of its sub-expressions. All other attributes are either shared between both types of expressions, or derived from the RT.
A 100% declarative language (i.e. one in which every possible expression is RT) does not (among other RT requirements) allow the mutation of stored values, e.g. HTML and most of Haskell.
Definition of RT expression
RT is often referred to as having "no side-effects". The term effects does not have a precise definition, so some people don't agree that "no side-effects" is the same as RT. RT has a precise definition:
An expression e is referentially transparent if for all programs p every occurrence of e in p can be replaced with the result of evaluating e, without affecting the observable result of p.
Since every sub-expression is conceptually a function call, RT requires that the implementation of a function (i.e. the expression(s) inside the called function) may not access the mutable state that is external to the function (accessing the mutable local state is allowed). Put simply, the function (implementation) should be pure.
Definition of pure function
A pure function is often said to have "no side-effects". The term effects does not have a precise definition, so some people don't agree.
Pure functions have the following attributes.
- the only observable output is the return value.
- the only output dependency is the arguments.
- arguments are fully determined before any output is generated.
Remember that RT applies to expressions (which includes function calls) and purity applies to (implementations of) functions.
An obscure example of impure functions that make RT expressions is concurrency, but this is because the purity is broken at the interrupt abstraction layer. You don't really need to know this. To make RT expressions, you call pure functions.
Derivative attributes of RT
Any other attribute cited for declarative programming, e.g. the citation from 1999 used by Wikipedia, either derives from RT, or is shared with imperative programming. Thus proving that my precise definition is correct.
Note, immutability of external values is a subset of the requirements for RT.
- Declarative languages don't have looping control structures, e.g. for and while , because due to immutability, the loop condition would never change.
- Declarative languages don't express control-flow other than nested function order (a.k.a logical dependencies), because due to immutability, other choices of evaluation order do not change the result (see below).
- Declarative languages express logical "steps" (i.e. the nested RT function call order), but whether each function call is a higher level semantic (i.e. "what to do") is not a requirement of declarative programming. The distinction from imperative is that due to immutability (i.e. more generally RT), these "steps" cannot depend on mutable state, rather only the relational order of the expressed logic (i.e. the order of nesting of the function calls, a.k.a. sub-expressions).
For example, the HTML paragraph <p> cannot be displayed until the sub-expressions (i.e. tags) in the paragraph have been evaluated. There is no mutable state, only an order dependency due to the logical relationship of tag hierarchy (nesting of sub-expressions, which are analogously nested function calls).
- Thus there is the derivative attribute of immutability (more generally RT), that declarative expressions, express only the logical relationships of the constituent parts (i.e. of the sub-expression function arguments) and not mutable state relationships.
Evaluation order
The choice of evaluation order of sub-expressions can only give a varying result when any of the function calls are not RT (i.e. the function is not pure), e.g. some mutable state external to a function is accessed within the function.
For example, given some nested expressions, e.g. f( g(a, b), h(c, d) ), eager and lazy evaluation of the function arguments will give the same results if the functions f, g, and h are pure.
Whereas, if the functions f, g, and h are not pure, then the choice of evaluation order can give a different result.
Note, nested expressions are conceptually nested functions, since expression operators are just function calls masquerading as unary prefix, unary postfix, or binary infix notation.
Tangentially, if all identifiers, e.g. a, b, c, d, are immutable everywhere, state external to the program cannot be accessed (i.e. I/O), and there is no abstraction layer breakage, then functions are always pure.
By the way, Haskell has a different syntax, f (g a b) (h c d).
Evaluation order details
A function is a state transition (not a mutable stored value) from the input to the output. For RT compositions of calls to pure functions, the order-of-execution of these state transitions is independent. The state transition of each function call is independent of the others, due to lack of side-effects and the principle that an RT function may be replaced by its cached value. To correct a popular misconception, pure monadic composition is always declarative and RT, in spite of the fact that Haskell's IO monad is arguably impure and thus imperative w.r.t. the World state external to the program (but in the sense of the caveat below, the side-effects are isolated).
Eager evaluation means the functions arguments are evaluated before the function is called, and lazy evaluation means the arguments are not evaluated until (and if) they are accessed within the function.
Definition: function parameters are declared at the function definition site, and function arguments are supplied at the function call site. Know the difference between parameter and argument.
Conceptually, all expressions are (a composition of) function calls, e.g. constants are functions without inputs, unary operators are functions with one input, binary infix operators are functions with two inputs, constructors are functions, and even control statements (e.g. if, for, while) can be modeled with functions. The order that these argument functions (do not confuse with nested function call order) are evaluated is not declared by the syntax, e.g. f( g() ) could eagerly evaluate g then f on g's result or it could evaluate f and only lazily evaluate g when its result is needed within f.
Caveat, no Turing complete language (i.e. that allows unbounded recursion) is perfectly declarative, e.g. lazy evaluation introduces memory and time indeterminism. But these side-effects due to the choice of evaluation order are limited to memory consumption, execution time, latency, non-termination, and external hysteresis thus external synchronization.
Functional programming
Because declarative programming cannot have loops, then the only way to iterate is functional recursion. It is in this sense that functional programming is related to declarative programming.
But functional programming is not limited to declarative programming. Functional composition can be contrasted with subtyping, especially with respect to the Expression Problem, where extension can be achieved by either adding subtypes or functional decomposition. Extension can be a mix of both methodologies.
Functional programming usually makes the function a first-class object, meaning the function type can appear in the grammar anywhere any other type may. The upshot is that functions can input and operate on functions, thus providing for separation-of-concerns by emphasizing function composition, i.e. separating the dependencies among the subcomputations of a deterministic computation.
For example, instead of writing a separate function (and employing recursion instead of loops if the function must also be declarative) for each of an infinite number of possible specialized actions that could be applied to each element of a collection, functional programming employs reusable iteration functions, e.g. map, fold, filter. These iteration functions input a first-class specialized action function. These iteration functions iterate the collection and call the input specialized action function for each element. These action functions are more concise because they no longer need to contain the looping statements to iterate the collection.
However, note that if a function is not pure, then it is really a procedure. We can perhaps argue that functional programming that uses impure functions, is really procedural programming. Thus if we agree that declarative expressions are RT, then we can say that procedural programming is not declarative programming, and thus we might argue that functional programming is always RT and must be a subset of declarative programming.
Parallelism
This functional composition with first-class functions can express the depth in the parallelism by separating out the independent function.
Brent’s Principle: computation with work w and depth d can be implemented in a p-processor PRAM in time O(max(w/p, d)).
Both concurrency and parallelism also require declarative programming, i.e. immutability and RT.
So where did this dangerous assumption that Parallelism == Concurrency come from? It’s a natural consequence of languages with side-effects: when your language has side-effects everywhere, then any time you try to do more than one thing at a time you essentially have non-determinism caused by the interleaving of the effects from each operation. So in side-effecty languages, the only way to get parallelism is concurrency; it’s therefore not surprising that we often see the two conflated.
FP evaluation order
Note the evaluation order also impacts the termination and performance side-effects of functional composition.
Eager (CBV) and lazy (CBN) are categorical duels[10], because they have reversed evaluation order, i.e. whether the outer or inner functions respectively are evaluated first. Imagine an upside-down tree, then eager evaluates from function tree branch tips up the branch hierarchy to the top-level function trunk; whereas, lazy evaluates from the trunk down to the branch tips. Eager doesn't have conjunctive products ("and", a/k/a categorical "products") and lazy doesn't have disjunctive coproducts ("or", a/k/a categorical "sums")[11].
Performance
- Eager
As with non-termination, eager is too eager with conjunctive functional composition, i.e. compositional control structure does unnecessary work that isn't done with lazy. For example, eager eagerly and unnecessarily maps the entire list to booleans, when it is composed with a fold that terminates on the first true element.
This unnecessary work is the cause of the claimed "up to" an extra log n factor in the sequential time complexity of eager versus lazy, both with pure functions. A solution is to use functors (e.g. lists) with lazy constructors (i.e. eager with optional lazy products), because with eager the eagerness incorrectness originates from the inner function. This is because products are constructive types, i.e. inductive types with an initial algebra on an initial fixpoint[11]
- Lazy
As with non-termination, lazy is too lazy with disjunctive functional composition, i.e. coinductive finality can occur later than necessary, resulting in both unnecessary work and non-determinism of the lateness that isn't the case with eager[10][11]. Examples of finality are state, timing, non-termination, and runtime exceptions. These are imperative side-effects, but even in a pure declarative language (e.g. Haskell), there is state in the imperative IO monad (note: not all monads are imperative!) implicit in space allocation, and timing is state relative to the imperative real world. Using lazy even with optional eager coproducts leaks "laziness" into inner coproducts, because with lazy the laziness incorrectness originates from the outer function (see the example in the Non-termination section, where == is an outer binary operator function). This is because coproducts are bounded by finality, i.e. coinductive types with a final algebra on an final object[11].
Lazy causes indeterminism in the design and debugging of functions for latency and space, the debugging of which is probably beyond the capabilities of the majority of programmers, because of the dissonance between the declared function hierarchy and the runtime order-of-evaluation. Lazy pure functions evaluated with eager, could potentially introduce previously unseen non-termination at runtime. Conversely, eager pure functions evaluated with lazy, could potentially introduce previously unseen space and latency indeterminism at runtime.
Non-termination
At compile-time, due to the Halting problem and mutual recursion in a Turing complete language, functions can't generally be guaranteed to terminate.
- Eager
With eager but not lazy, for the conjunction of Head "and" Tail, if either Head or Tail doesn't terminate, then respectively either List( Head(), Tail() ).tail == Tail() or List( Head(), Tail() ).head == Head() is not true because the left-side doesn't, and right-side does, terminate.
Whereas, with lazy both sides terminate. Thus eager is too eager with conjunctive products, and non-terminates (including runtime exceptions) in those cases where it isn't necessary.
- Lazy
With lazy but not eager, for the disjunction of 1 "or" 2, if f doesn't terminate, then List( f ? 1 : 2, 3 ).tail == (f ? List( 1, 3 ) : List( 2, 3 )).tail is not true because the left-side terminates, and right-side doesn't.
Whereas, with eager neither side terminates so the equality test is never reached. Thus lazy is too lazy with disjunctive coproducts, and in those cases fails to terminate (including runtime exceptions) after doing more work than eager would have.
[10] Declarative Continuations and Categorical Duality, Filinski, sections 2.5.4 A comparison of CBV and CBN, and 3.6.1 CBV and CBN in the SCL.
[11] Declarative Continuations and Categorical Duality, Filinski, sections 2.2.1 Products and coproducts, 2.2.2 Terminal and initial objects, 2.5.2 CBV with lazy products, and 2.5.3 CBN with eager coproducts.
Other Answers
Answered Feb 02, 2017 · 106 votes
There's not really any non-ambiguous, objective definition for these. Here is how I would define them:
Imperative - The focus is on what steps the computer should take rather than what the computer will do (ex. C, C++, Java).
Declarative - The focus is on what the computer should do rather than how it should do it (ex. SQL).
Functional - a subset of declarative languages that has heavy focus on recursion
Other Answers
Answered Jul 04, 2012 · 62 votes
imperative and declarative describe two opposing styles of programming. imperative is the traditional "step by step recipe" approach while declarative is more "this is what i want, now you work out how to do it".
these two approaches occur throughout programming - even with the same language and the same program. generally the declarative approach is considered preferable, because it frees the programmer from having to specify so many details, while also having less chance for bugs (if you describe the result you want, and some well-tested automatic process can work backwards from that to define the steps then you might hope that things are more reliable than having to specify each step by hand).
on the other hand, an imperative approach gives you more low level control - it's the "micromanager approach" to programming. and that can allow the programmer to exploit knowledge about the problem to give a more efficient answer. so it's not unusual for some parts of a program to be written in a more declarative style, but for the speed-critical parts to be more imperative.
as you might imagine, the language you use to write a program affects how declarative you can be - a language that has built-in "smarts" for working out what to do given a description of the result is going to allow a much more declarative approach than one where the programmer needs to first add that kind of intelligence with imperative code before being able to build a more declarative layer on top. so, for example, a language like prolog is considered very declarative because it has, built-in, a process that searches for answers.
so far, you'll notice that i haven't mentioned functional programming. that's because it's a term whose meaning isn't immediately related to the other two. at its most simple, functional programming means that you use functions. in particular, that you use a language that supports functions as "first class values" - that means that not only can you write functions, but you can write functions that write functions (that write functions that...), and pass functions to functions. in short - that functions are as flexible and common as things like strings and numbers.
it might seem odd, then, that functional, imperative and declarative are often mentioned together. the reason for this is a consequence of taking the idea of functional programming "to the extreme". a function, in it's purest sense, is something from maths - a kind of "black box" that takes some input and always gives the same output. and that kind of behaviour doesn't require storing changing variables. so if you design a programming language whose aim is to implement a very pure, mathematically influenced idea of functional programming, you end up rejecting, largely, the idea of values that can change (in a certain, limited, technical sense).
and if you do that - if you limit how variables can change - then almost by accident you end up forcing the programmer to write programs that are more declarative, because a large part of imperative programming is describing how variables change, and you can no longer do that! so it turns out that functional programming - particularly, programming in a functional language - tends to give more declarative code.
to summarise, then:
- ["imperative and declarative are two opposing styles of programming (the same names are used for programming languages that encourage those styles)",""]
- ["functional programming is a style of programming where functions become very important and, as a consequence, changing values become less important. the limited ability to specify changes in values forces a more declarative style.",""]
so "functional programming" is often described as "declarative".
1/5
Top Answer
Answered Aug 22, 2017 · 189 votes
Definition: An imperative language uses a sequence of statements to determine how to reach a certain goal. These statements are said to change the state of the program as each one is executed in turn.
Examples: Java is an imperative language. For example, a program can be created to add a series of numbers:
int total = 0; int number1 = 5; int number2 = 10; int number3 = 15; total = number1 + number2 + number3;
Each statement changes the state of the program, from assigning values to each variable to the final addition of those values. Using a sequence of five statements the program is explicitly told how to add the numbers 5, 10 and 15 together.
Functional languages: The functional programming paradigm was explicitly created to support a pure functional approach to problem solving. Functional programming is a form of declarative programming.
Advantages of Pure Functions: The primary reason to implement functional transformations as pure functions is that pure functions are composable: that is, self-contained and stateless. These characteristics bring a number of benefits, including the following: Increased readability and maintainability. This is because each function is designed to accomplish a specific task given its arguments. The function does not rely on any external state.
Easier reiterative development. Because the code is easier to refactor, changes to design are often easier to implement. For example, suppose you write a complicated transformation, and then realize that some code is repeated several times in the transformation. If you refactor through a pure method, you can call your pure method at will without worrying about side effects.
Easier testing and debugging. Because pure functions can more easily be tested in isolation, you can write test code that calls the pure function with typical values, valid edge cases, and invalid edge cases.
For OOP People or Imperative languages:
Object-oriented languages are good when you have a fixed set of operations on things and as your code evolves, you primarily add new things. This can be accomplished by adding new classes which implement existing methods and the existing classes are left alone.
Functional languages are good when you have a fixed set of things and as your code evolves, you primarily add new operations on existing things. This can be accomplished by adding new functions which compute with existing data types and the existing functions are left alone.
Cons:
It depends on the user requirements to choose the way of programming, so there is harm only when users don’t choose the proper way.
When evolution goes the wrong way, you have problems:
- Adding a new operation to an object-oriented program may require editing many class definitions to add a new method
- Adding a new kind of thing to a functional program may require editing many function definitions to add a new case.
Other Answers
Answered Feb 02, 2017 · 106 votes
There's not really any non-ambiguous, objective definition for these. Here is how I would define them:
Imperative - The focus is on what steps the computer should take rather than what the computer will do (ex. C, C++, Java).
Declarative - The focus is on what the computer should do rather than how it should do it (ex. SQL).
Functional - a subset of declarative languages that has heavy focus on recursion
Other Answers
Answered Jul 04, 2012 · 62 votes
imperative and declarative describe two opposing styles of programming. imperative is the traditional "step by step recipe" approach while declarative is more "this is what i want, now you work out how to do it".
these two approaches occur throughout programming - even with the same language and the same program. generally the declarative approach is considered preferable, because it frees the programmer from having to specify so many details, while also having less chance for bugs (if you describe the result you want, and some well-tested automatic process can work backwards from that to define the steps then you might hope that things are more reliable than having to specify each step by hand).
on the other hand, an imperative approach gives you more low level control - it's the "micromanager approach" to programming. and that can allow the programmer to exploit knowledge about the problem to give a more efficient answer. so it's not unusual for some parts of a program to be written in a more declarative style, but for the speed-critical parts to be more imperative.
as you might imagine, the language you use to write a program affects how declarative you can be - a language that has built-in "smarts" for working out what to do given a description of the result is going to allow a much more declarative approach than one where the programmer needs to first add that kind of intelligence with imperative code before being able to build a more declarative layer on top. so, for example, a language like prolog is considered very declarative because it has, built-in, a process that searches for answers.
so far, you'll notice that i haven't mentioned functional programming. that's because it's a term whose meaning isn't immediately related to the other two. at its most simple, functional programming means that you use functions. in particular, that you use a language that supports functions as "first class values" - that means that not only can you write functions, but you can write functions that write functions (that write functions that...), and pass functions to functions. in short - that functions are as flexible and common as things like strings and numbers.
it might seem odd, then, that functional, imperative and declarative are often mentioned together. the reason for this is a consequence of taking the idea of functional programming "to the extreme". a function, in it's purest sense, is something from maths - a kind of "black box" that takes some input and always gives the same output. and that kind of behaviour doesn't require storing changing variables. so if you design a programming language whose aim is to implement a very pure, mathematically influenced idea of functional programming, you end up rejecting, largely, the idea of values that can change (in a certain, limited, technical sense).
and if you do that - if you limit how variables can change - then almost by accident you end up forcing the programmer to write programs that are more declarative, because a large part of imperative programming is describing how variables change, and you can no longer do that! so it turns out that functional programming - particularly, programming in a functional language - tends to give more declarative code.
to summarise, then:
- ["imperative and declarative are two opposing styles of programming (the same names are used for programming languages that encourage those styles)",""]
- ["functional programming is a style of programming where functions become very important and, as a consequence, changing values become less important. the limited ability to specify changes in values forces a more declarative style.",""]
so "functional programming" is often described as "declarative".
2/5
Top Answer
Answered Dec 29, 2017 · 2 votes
Let’s use this simple code: a = b + c to examine the difference.
When we write a = b + c in an imperative language, like C, we are assigning the current value of b + c to the variable a and nothing more. We aren’t making any fundamental statement about what a is. Rather, we are simply executing a step in a process.
When we write a = b + c in a declarative language, like Microsoft Excel, we are asserting a relationship between a, b and c such that it is always the case that a is the sum of the other two. It’s not a step in a process, it’s an invariant, a guarantee, a declaration of truth.
Functional languages are declarative as well, but almost by accident. In Haskel for example a = b + c also asserts an invariant relationship, but only because b and c are immutable.
3/5
Top Answer
Answered Jan 26, 2021 · 130 votes
Your example of declarative programming above is not an actual program, so it's not a good example.
The main difference is between imperative and declarative. Functional is a particular kind of declarative.
C, C++, Java, Javascript, BASIC, Python, Ruby, and most other programming languages are imperative. As a rule, if it has explicit loops (for, while, repeat) that change variables with explicit assignment operations at each loop, then it's imperative.
SQL and XSLT are two well-known examples of declarative programming. Markup languages such as HTML and CSS are declarative too, although they are usually not powerful enough to describe arbitrary algorithms.
Here is an example computation (summing the income by gender, from a suitable data source) first written in an imperative language (Javascript) and then in a declarative language (SQL).
Imperative programming
var income_m = 0, income_f = 0;for (var i = 0; i < income_list.length; i++) { if (income_list[i].gender == 'M') income_m += income_list[i].income; else income_f += income_list[i].income;}
Notice:
- explicit initialization of variables that will contain the running totals;
- explicit loop over the data, modifying the control variable ( i) and the running totals at each iteration;
- conditionals ( ifs) are only used to choose the code path at each iteration.
Declarative programming
select gender, sum(income)from income_listgroup by gender;
Notice:
- memory cells to contain running totals are implied by the output you declare you want;
- any loop the CPU will need to perform (eg. over the income_list table) is implied by the output you declare you want and by the structure of the source data;
- conditionals (eg. case in SQL) are used in a functional way to specify the output value you want based on the input values, not to choose a code path.
Functional programming
As I mentioned above, SQL's case is a great example of the functional way of programming, which is a restricted subset of Declarative programming in which the desired computation is specified by composing functions.
Functions are things that accept inputs and return outputs (eg. case, sum()…)
Composition means chaining two or more together by specifying how the output of one is fed as the input to the next (typically by writing one inside the other.) Finally the whole composition, which is still itself a big function, is applied to the available inputs to get the desired output.
In this snippet I am declaring the output I want by composing the functions sum() and case. This is called functional programming:
select sum(case when some_flag = 'X' then some_column else some_other_column end)from ...
If the composition of two or more functions and their application to the input data are the only constructs available in a given language, that language is said to be purely functional. In those languages you will notice the complete absence of loops, variable assignment and other typically imperative statements.
Edit: I recommend watching some of Anjana Vakil's talks on functional programming in Javascript, to get a better idea of what it's about.
4/5
Top Answer
Answered Aug 23, 2008 · 94 votes
One key feature in a functional language is the concept of first-class functions. The idea is that you can pass functions as parameters to other functions and return them as values.
Functional programming involves writing code that does not change state. The primary reason for doing so is so that successive calls to a function will yield the same result. You can write functional code in any language that supports first-class functions, but there are some languages, like Haskell, which do not allow you to change state. In fact, you're not supposed to make any side effects (like printing out text) at all - which sounds like it could be completely useless.
Haskell instead employs a different approach to IO: monads. These are objects that contain the desired IO operation to be executed by your interpreter's toplevel. At any other level they are simply objects in the system.
What advantages does functional programming provide? Functional programming allows coding with fewer potentials for bugs because each component is completely isolated. Also, using recursion and first-class functions allows for simple proofs of correctness which typically mirror the structure of the code.
Other Answers
Answered Feb 02, 2017 · 106 votes
There's not really any non-ambiguous, objective definition for these. Here is how I would define them:
Imperative - The focus is on what steps the computer should take rather than what the computer will do (ex. C, C++, Java).
Declarative - The focus is on what the computer should do rather than how it should do it (ex. SQL).
Functional - a subset of declarative languages that has heavy focus on recursion
Other Answers
Answered Jul 04, 2012 · 62 votes
imperative and declarative describe two opposing styles of programming. imperative is the traditional "step by step recipe" approach while declarative is more "this is what i want, now you work out how to do it".
these two approaches occur throughout programming - even with the same language and the same program. generally the declarative approach is considered preferable, because it frees the programmer from having to specify so many details, while also having less chance for bugs (if you describe the result you want, and some well-tested automatic process can work backwards from that to define the steps then you might hope that things are more reliable than having to specify each step by hand).
on the other hand, an imperative approach gives you more low level control - it's the "micromanager approach" to programming. and that can allow the programmer to exploit knowledge about the problem to give a more efficient answer. so it's not unusual for some parts of a program to be written in a more declarative style, but for the speed-critical parts to be more imperative.
as you might imagine, the language you use to write a program affects how declarative you can be - a language that has built-in "smarts" for working out what to do given a description of the result is going to allow a much more declarative approach than one where the programmer needs to first add that kind of intelligence with imperative code before being able to build a more declarative layer on top. so, for example, a language like prolog is considered very declarative because it has, built-in, a process that searches for answers.
so far, you'll notice that i haven't mentioned functional programming. that's because it's a term whose meaning isn't immediately related to the other two. at its most simple, functional programming means that you use functions. in particular, that you use a language that supports functions as "first class values" - that means that not only can you write functions, but you can write functions that write functions (that write functions that...), and pass functions to functions. in short - that functions are as flexible and common as things like strings and numbers.
it might seem odd, then, that functional, imperative and declarative are often mentioned together. the reason for this is a consequence of taking the idea of functional programming "to the extreme". a function, in it's purest sense, is something from maths - a kind of "black box" that takes some input and always gives the same output. and that kind of behaviour doesn't require storing changing variables. so if you design a programming language whose aim is to implement a very pure, mathematically influenced idea of functional programming, you end up rejecting, largely, the idea of values that can change (in a certain, limited, technical sense).
and if you do that - if you limit how variables can change - then almost by accident you end up forcing the programmer to write programs that are more declarative, because a large part of imperative programming is describing how variables change, and you can no longer do that! so it turns out that functional programming - particularly, programming in a functional language - tends to give more declarative code.
to summarise, then:
- ["imperative and declarative are two opposing styles of programming (the same names are used for programming languages that encourage those styles)",""]
- ["functional programming is a style of programming where functions become very important and, as a consequence, changing values become less important. the limited ability to specify changes in values forces a more declarative style.",""]
so "functional programming" is often described as "declarative".
5/5
stackoverflow.com › questions › 17826380oop - What is difference between functional and imperative ...
stackoverflow.com › questions › 17826380Most modern languages are in varying degree both imperative and functional but to better understand functional programming, it will be best to take an example of pure functional language like Haskell in contrast of imperative code in not so functional language like java/C#.
- The Fibonaccis
Code sample
int total = 0;int number1 = 5;int number2 = 10;int number3 = 15;total = number1 + number2 + number3;www.geeksforgeeks.org › difference-betweenDifference between Functional and Imperative Programming
www.geeksforgeeks.org › difference-betweenMar 15, 2021 · Difference between Functional and Imperative Programming. Last Updated : 15 Mar, 2021. Functional Programming: Functional Programming, as the name suggests, is a type of programming paradigm that is being created explicitly simply to support a purely functional approach to solving problems.
Functional ProgrammingImperative ProgrammingIt is generally a process of developing ...It is generally a process of describing ...It mainly focuses on what programs should ...It mainly focuses on describing how the ...It uses functions to perform everything.It uses statements that change a ...Its advantages include bugs-free code, ...Its advantages include easy to learn, ...People also ask
What is the difference between imperative and functional programming?
- With an imperative approach, a developer writes code that specifies the steps that the computer must take to accomplish the goal. This is sometimes referred to as algorithmic programming. In contrast, a functional approach involves composing the problem as a set of functions to be executed.
Functional programming vs. imperative programming (LINQ to XML)
learn.microsoft.com/en-us/dotnet/standard/linq/functional-vs-imperative-programmingWhat languages support imperative programming?
- In contrast, most mainstream languages, including object-oriented programming (OOP) languages such as C#, Visual Basic, C++, and Java, were designed to primarily support imperative (procedural) programming. With an imperative approach, a developer writes code that specifies the steps that the computer must take to accomplish the goal.
Functional programming vs. imperative programming (LINQ to XML)
learn.microsoft.com/en-us/dotnet/standard/linq/functional-vs-imperative-programmingWhy are functional programming languages less efficient than imperative programming languages?
- Functional programming languages are typically less efficient in their use of CPU and memory than imperative languages such as C and Pascal. This is related to the fact that some mutable data structures like arrays have a very straightforward implementation using present hardware.
Functional programming - Wikipedia
en.wikipedia.org/wiki/Functional_programmingWhat is imperative programming?
- Imperative Programming: Imperative Programming, as the name suggests, is a type of programming paradigm that specifies steps that computers should take to complete or finish a goal. In this, functions are coded implicitly in each and every step that is required to solve a problem. In simple words, it includes commands for the computer to perform.
Difference between Functional and Imperative Programming
www.geeksforgeeks.org/difference-between-functional-and-imperative-programming/www.digitalocean.com › community › tutorialsCompare Functional Programming, Imperative Programming and ...
www.digitalocean.com › community › tutorialsAug 3, 2022 · Functional Programming (FP) Imperative Programming (IP) Object Oriented Programming (OOP) What is Functional Programming? In simple words, Functional Programming (FP) is one of the popular Programming paradigms, which does computation like Mathematical Functions without Changing State and Mutating Data. In Functional Programming, Functions are ...
learn.microsoft.com › en-us › dotnetFunctional programming vs. imperative programming - LINQ to ...
learn.microsoft.com › en-us › dotnetSep 15, 2021 · In contrast, most mainstream languages, including object-oriented programming (OOP) languages such as C#, Visual Basic, C++, and Java, were designed to primarily support imperative (procedural) programming. With an imperative approach, a developer writes code that specifies the steps that the computer must take to accomplish the goal.
en.wikipedia.org › wiki › Functional_programmingFunctional programming - Wikipedia
en.wikipedia.org › wiki › Functional_programmingStrict versus non-strict evaluation. Type systems. Referential transparency. Data structures. Comparison to imperative programming. Imperative vs. functional programming. Simulating state. Efficiency issues. Abstraction cost. Functional programming in non-functional languages. Comparison to logic programming. Applications. Text editors.
www.freecodecamp.org › news › an-introduction-toProgramming Paradigms – Paradigm Examples for Beginners
www.freecodecamp.org › news › an-introduction-toMay 2, 2022 · Functional programming. Declarative programming. Object-oriented programming. Roundup. What is a Programming Paradigm? Programming paradigms are different ways or styles in which a given program or programming language can be organized.
en.wikipedia.org › wiki › Comparison_of_programmingComparison of programming paradigms - Wikipedia
en.wikipedia.org › wiki › Comparison_of_programmingImperative programming – focuses on how to execute, defines control flow as statements that change a program state. Declarative programming – focuses on what to execute, defines program logic, but not detailed control flow. The following are widely considered the main programming paradigms, as seen when measuring programming language popularity:
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