First-class citizen

First-class function

In computer science, a programming language is said to have first-class functions if it treats functions as first-class citizens. Specifically, this means the language supports passing functions as arguments to other functions, returning them as the values from other functions, and assigning them to variables or storing them in data structures.^[1] Some programming language theorists require support for anonymous functions(function literals) as well.^[2] In languages with first-class functions, the names of functions do not have any special status; they are treated like ordinary variables with a function type.^[3] The term was coined byChristopher Strachey in the context of “functions as first-class citizens” in the mid-1960s.^[4]

First-class functions are a necessity for the functional programming style, in which the use of higher-order functions is a standard practice. A simple example of a higher-ordered function is the map function, which takes, as its arguments, a function and a list, and returns the list formed by applying the function to each member of the list. For a language to support map, it must support passing a function as an argument.

There are certain implementation difficulties in passing functions as arguments and returning them as results, especially in the presence of non-local variables introduced in nested and anonymous functions. Historically, these were termed the funarg problems, the name coming from "function argument".^[5] In early imperative languages these problems were avoided by either not supporting functions as result types (e.g. ALGOL 60, Pascal) or omitting nested functions and thus non-local variables (e.g. C). The early functional language Lisp took the approach of dynamic scoping, where non-local variables refer to the closest definition of that variable at the point where the function is executed, instead of where it was defined. Proper support for lexically scoped first-class functions was introduced in Scheme and requires handling references to functions as closures instead of bare function pointers,^[4] which in turn makes garbage collection a necessity.

Concepts[edit]

In this section we compare how particular programming idioms are handled in a functional language with first-class functions (Haskell) compared to an imperative language where functions are second-class citizens (C).

Higher-order functions: passing functions as arguments[edit]

In languages where functions are first-class citizens, functions can be passed as arguments to other functions in the same way as other values (a function taking another function as argument is called a higher-order function). In the language Haskell:

map :: (a -> b) -> [a] -> [b]
map f []     = []
map f (x:xs) = f x : map f xs

Languages where functions are not first-class often still allow one to write higher-order functions through the use of features such as function pointers or delegates. In the language C:

void map(int (*f)(int), int x[], size_t n) {
    for (int i = 0; i < n; i++)
        x[i] = f(x[i]);
}

When comparing the two samples, one should note that there are a number of differences between the two approaches that are not directly related to the support of first-class functions. The Haskell sample operates on lists, while the C sample operates on arrays. Both are the most natural compound data structures in the respective languages and making the C sample operate on linked lists would have made it unnecessarily complex. This also accounts for the fact that the C function needs an additional parameter (giving the size of the array.) The C function updates the array in-place, returning no value, whereas in Haskell data structures are persistent (a new list is returned while the old is left intact.) The Haskell sample uses recursion to traverse the list, while the C sample uses iteration. Again, this is the most natural way to express this function in both languages, but the Haskell sample could easily have been expressed in terms of a fold and the C sample in terms of recursion. Finally, the Haskell function has a polymorphic type, as this is not supported by C we have fixed all type variables to the type constant int.

Anonymous and nested functions[edit]

In languages supporting anonymous functions, we can pass such a function as an argument to a higher-order function:

main = map (\x -> 3 * x + 1) [1, 2, 3, 4, 5]

In a language which does not support anonymous functions, we have to bind it to a name instead:

int f(int x) {
    return 3 * x + 1;
}

int main() {
    int list[] = {1, 2, 3, 4, 5};
    map(f, list, 5);
}

Non-local variables and closures[edit]

Once we have anonymous or nested functions, it becomes natural for them to refer to variables outside of their body (called non-local variables):

main = let a = 3
           b = 1
        in map (\x -> a * x + b) [1, 2, 3, 4, 5]

If functions are represented with bare function pointers, it is no longer obvious how we should pass the value outside of the function body to it. We instead have to manually build a closure and one can at this point no longer speak of "first-class" functions.

typedef struct {
    int (*f)(int, int, int);
    int *a;
    int *b;
} closure_t;

void map(closure_t *closure, int x[], size_t n) {
    for (int i = 0; i < n; ++i)
        x[i] = (*closure->f)(*closure->a, *closure->b, x[i]);
}

int f(int a, int b, int x) {
    return a * x + b;
}

void main() {
    int l[] = {1, 2, 3, 4, 5};
    int a = 3;
    int b = 1;
    closure_t closure = {f, &a, &b};
    map(&closure, l, 5);
}

Also note that the map is now specialized to functions referring to two ints outside of their environment. This can be set up more generally, but requires more boilerplate code. If f would have been a nested function we would still have run into the same problem and this is the reason they are not supported in C.^[6]

Higher-order functions: returning functions as results[edit]

When returning a function, we are in fact returning its closure. In the C example any local variables captured by the closure will go out of scope once we return from the function that builds the closure. Forcing the closure at a later point will result in undefined behaviour, possibly corrupting the stack. This is known as the upwards funarg problem.

Assigning functions to variables[edit]

Assigning functions to variables and storing them inside (global) datastructures potentially suffers from the same difficulties as returning functions.

f :: [[Integer] -> [Integer]]
f = let a = 3
        b = 1
     in [map (\x -> a * x + b), map (\x -> b * x + a)]

Equality of functions[edit]

As one can test most literals and values for equality, it is natural to ask whether a programming language can support testing functions for equality. On further inspection, this question appears more difficult and one has to distinguish between several types of function equality:^[7]

Extensional equality

Two functions f and g are considered extensionally equal if they agree on their outputs for all inputs (∀x. f(x) = g(x)). Under this definition of equality, for example, any two implementations of a stable sorting algorithm, such as insertion sort and merge sort, would be considered equal. Deciding on extensional equality is undecidable in general and even for functions with finite domains often intractable. For this reason no programming language implements function equality as extensional equality.

Intensional equality

Under intensional equality, two functions f and g are considered equal if they have the same "internal structure". This kind of equality could be implemented in interpreted languages by comparing the source code of the function bodies (such as in Interpreted Lisp 1.5) or the object code in compiled languages. Intensional equality implies extensional equality (under the assumption that the functions do not depend on the value of the program counter.)

Reference equality

Given the impracticality of implementing extensional and intensional equality, most languages supporting testing functions for equality use reference equality. All functions or closures are assigned a unique identifier (usually the address of the function body or the closure) and equality is decided based on equality of the identifier. Two separately defined, but otherwise identical function definitions will be considered unequal. Referential equality implies intensional and extensional equality. Referential equality breaks referential transparency and is therefore not supported in pure languages, such as Haskell.

Type theory[edit]

In type theory, the type of functions accepting values of type A and returning values of type B may be written as A → B or B^A. In the Curry-Howard correspondence, function types are related to logical implication; lambda abstraction corresponds to discharging hypothetical assumptions and function application corresponds to the modus ponens inference rule. Besides the usual case of programming functions, type theory also uses first-class functions to model associative arrays and similar data structures.

In category-theoretical accounts of programming, the availability of first-class functions corresponds to the closed category assumption. For instance, the simply typed lambda calculus corresponds to the internal language of cartesian closed categories.

Language support[edit]

Functional programming languages, such as Scheme, ML, Haskell, F#, and Scala, all have first-class functions. When Lisp, one of the earliest functional languages, was designed, not all aspects of first-class functions were then properly understood, resulting in functions being dynamically scoped. The later Common Lisp dialect does have lexically scoped first-class functions.

Many scripting languages, including Perl, Python, PHP, Lua, Tcl/Tk, JavaScript and Io, have first-class functions.

For imperative languages, a distinction has to be made between Algol and its descendants such as Pascal, the traditional C family, and the modern garbage-collected variants. The Algol family has allowed nested functions and higher-order taking function as arguments, but not higher-order functions that return functions as results (except Algol 68, which allows this). The reason for this was that it was not known how to deal with non-local variables if a nested-function was returned as a result (and Algol 68 produces runtime errors in such cases).

The C family allowed both passing functions as arguments and returning them as results, but avoided any problems by not supporting nested functions. (The gcc compiler allows them as an extension.) As the usefulness of returning functions primarily lies in the ability to return nested functions that have captured non-local variables, instead of top-level functions, these languages are generally not considered to have first-class functions.

Modern imperative languages often support garbage-collection making the implementation of first-class functions feasible. First-class function have often only been supported in later revisions of the language, including C# 2.0 and Apple's Blocks extension to C, C++ and Objective-C. C++11 has added support for anonymous functions and closures to the language, but because of the non-garbage collected nature of the language, special care has to be taken for non-local variables in functions to be returned as results (see below).

C++

C++11 closures can capture non-local variables by reference (without extending their lifetime), by copy construction or by move construction (the variable lives as long as the closure does). The former potentially avoids an expensive copy and allows to modify the original variable but is unsafe in case the closure is returned (see dangling references). The second is safe if the closure is returned but requires a copy and cannot be used to modify the original variable (which might not exist any more at the time the closure is called). The later is safe if the closure is returned and does not require a copy but cannot be used to modify the original variable either.

Java

Java 8 closures can only capture immutable ("effectively final") non-local variables. There are no function types in Java; in Java 8, anonymous functions take the type inferred from the context, which must be a "functional interface" (an interface with one method).

Lisp

Lexically scoped Lisp variants support closures. Dynamically scoped variants do not support closures or need a special construct to create closures.^[18]

In Common Lisp, the identifier of a function in the function namespace cannot be used as a reference to a first-class value. The special operator function must be used to retrieve the function as a value:(function foo) evaluates to a function object. #'foo exists as a shorthand notation. To apply such a function object, one must use the funcall function: (funcall #'foo bar baz).

Perl

Perl 5 only allows anonymous functions to be nested.

Python

Python's anonymous functions can only have an expression as the body.

Explicit partial application with functools.partial since version 2.5, and operator.methodcaller since version 2.6.

Ruby

The identifier of a regular "function" in Ruby (which is really a method) cannot be used as a value or passed. It must first be retrieved into a Method or Proc object to be used as first-class data. The syntax for calling such a function object differs from calling regular methods.

Nested method definitions do not actually nest the scope.

Explicit currying with [1].

See also[edit]

• Defunctionalization
• eval
• First-class message
• Kappa calculus – a formalism which excludes first-class functions
• Man or boy test
• Partial application

Notes[edit]

References[edit]

• Leonidas Fegaras. "Functional Languages and Higher-Order Functions". CSE5317/CSE4305: Design and Construction of Compilers. University of Texas at Arlington.

External links[edit]

• First-class functions on Rosetta Code.
• Higher order functions at IBM developerWorks

source - https://en.wikipedia.org/wiki/First-class_citizen

https://en.wikipedia.org/wiki/First-class_function

In computing, a data segment (often denoted .data) is a portion of an object file or the corresponding virtual address space of a program that contains initialized static variables, that is, global variables and static local variables. The size of this segment is determined by the size of the values in the program's source code, and does not change at run time.

The data segment is read-write, since the values of variables can be altered at run time. This is in contrast to the read-only data segment (rodata segment or .rodata), which contains static constants rather than variables; it also contrasts to the code segment, also known as the text segment, which is read-only on many architectures. Uninitialized data, both variables and constants, is instead in the BSS segment.

The PC architecture supports a few basic read-write memory regions in a program: stack, data and code. The heap is another region of address space available to a program, from which memory can be dynamically allocated or freed by the operating system in response to system calls such as malloc and free.

Program memory[edit]

The computer program memory is organized into the data segment (data and BSS), heap, stack, and code segment, as further explained below.

Data[edit]

The data area contains global and static variables used by the program that are explicitly initialized with a non-zero (or non-NULL) value. This segment can be further classified into a read-only area and read-write area. For instance, the string defined by char s[] = "hello world" in C, or a C statement like int debug = 1 outside the main function, would be stored in initialized read-write area. Also, a C statement like const char* string = "hello world", placed outside the main function, stores the string literal "hello world" in the read-only area (however, some C implementations may store it in the code segment instead), and the character pointer variable string in initialized read-write area.

The BSS segment, also known as uninitialized data, is usually adjacent to the data segment. The BSS segment contains all global variables and static variables that are initialized to zero or do not have explicit initialization in source code. For instance, a variable defined as static int i; would be contained in the BSS segment.

Heap[edit]

The heap area commonly begins at the end of the .bss and .data segments and grows to larger addresses from there. The heap area is managed by malloc, realloc, and free, which may use the brk and sbrk system calls to adjust its size (note that the use of brk/sbrk and a single "heap area" is not required to fulfill the contract of malloc/realloc/free; they may also be implemented using mmap to reserve potentially non-contiguous regions of virtual memory into the process' virtual address space). The heap area is shared by all threads, shared libraries, and dynamically loaded modules in a process.

Stack[edit]

The stack area contains the program stack, a LIFO structure, typically located in the higher parts of memory. A "stack pointer" register tracks the top of the stack; it is adjusted each time a value is "pushed" onto the stack. The set of values pushed for one function call is termed a "stack frame". A stack frame consists at minimum of a return address. Automatic variables are also allocated on the stack.

The stack area traditionally adjoined the heap area and they grew towards each other; when the stack pointer met the heap pointer, free memory was exhausted. With large address spaces and virtual memory techniques they tend to be placed more freely, but they still typically grow in opposite directions. On the standard PC x86 architecture the stack grows toward address zero, meaning that more recent items, deeper in the call chain, are at numerically lower addresses and closer to the heap. On some other architectures it grows the opposite direction.

Interpreted languages[edit]

Some interpreted languages offer a similar facility to the data segment, notably Perl^[1] and Ruby.^[2] In these languages, including the line __DATA__ (Perl) or __END__ (Ruby, old Perl) marks the end of the code segment and the start of the data segment. Only the contents prior to this line are executed, and the contents of the source file after this line are available as a file object: PACKAGE::DATA in Perl (e.g., main::DATA) andDATA in Ruby. This can be considered a form of here document (a file literal).

See also[edit]

• Segmentation (memory)
• Linker (computing)
• Code segment
• .bss
• Uninitialized variable
• Stack (abstract data type)

References[edit]

External links[edit]

• mem_sequence.c - sequentially lists memory regions in a process
• Expert C Programming: Deep C Secrets, Peter van der Linden, Prentice Hall 1997, p. 119ff
• Understanding Memory
• Code Segment and Data Segment: Memory Layout of a Program

In computing, a code segment, also known as a text segment or simply as text, is a portion of an object file or the corresponding section of the program's virtual address space that contains executable instructions.^[1] The term "segment" comes from the memory segment, which is a historical approach to memory management now known as paging. When a program is stored in an object file, the code segment is a part of this file; when the loader places a program into memory so that it may be executed, various memory regions are allocated (in particular, as pages), corresponding to both the segments in the object files and to segments only needed at run time. For example, the code segment of an object file is loaded into a corresponding code segment in memory.

The code segment in memory is typically read-only and has a fixed size, so on embedded systems it can usually be placed in read-only memory (ROM), without the need for loading. If the code segment is not read-only, then the particular architecture allows self-modifying code. Fixed-position or position independent code may be shared in memory by several processes in segmented or paged memory systems.^[1][2] As a memory region, the code segment may be placed below the heap or stack in order to prevent heap and stack overflows from overwriting it.^[3]

See also[edit]

Computer programming portal

• .bss
• Data segment
• Segmentation (memory)

References[edit]

source - https://en.wikipedia.org/wiki/Data_segment

https://en.wikipedia.org/wiki/Code_segment

What is the difference between reboot , init 6 and shutdown -r now?

Q.

I just want to know difference between in

• reboot
• init 6
• shutdown -r now

and which is the safest and the best?

A.

There is no difference in them. Internally they do exactly the same thing:

• reboot uses the shutdown command (with the -r switch). The shutdown command used to kill all the running processes, unmount all the file systems and finally tells the kernel to issue the ACPI power command. The source can be found here. In older distros the reboot command was forcing the processes to exit by issuing the SIGKILL signal (still found in sources, can be invoked with -f option), in most recent distros it defaults to the more graceful and init friendly init 1 -> shutdown -r. This ensures that daemons clean up themselves before shutdown.

• init 6 tells the init process to shutdown all of the spawned processes/daemons as written in the init files (in the inverse order they started) and lastly invoke the shutdown -r nowcommand to reboot the machine

Today there is not much difference as both commands do exactly the same, and they respect the init scripts used to start services/daemons by invoking the shutdown scripts for them. Except for reboot -f -r now as stated below

There is a small explanation taken from manpages of why the reboot -f is not safe:

  -f, --force
    Force immediate halt, power-off, reboot. Don't contact the init system.

Edit:

Forgot to mention, in upcoming RHEL distributions you should use the new systemctl command to issue poweroff/reboot. As stated in the manpages of reboot and shutdown they are a legacy command available for compatibility only. and the systemctl method will be the only one safe.

source - http://unix.stackexchange.com/questions/64280/what-is-the-difference-between-reboot-init-6-and-shutdown-r-now