Mimir:Draft4 Chapter4

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Chapter 4: Functional Programming

"Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot." - Eric Raymond

In this chapter you will learn:

  1. Functional Programming Concepts
  2. LISP Programming Language


Functional programming is one of several paradigms that has been defined in the different categorical classifications of programming languages. Functional Programming is commonly described as a paradigm that is similar to the evaluation of functions or similar to mathematical notation. Functional Programming does not use state changes of variables during execution. Many other paradigms are extensions to imperative programming such as procedural, object and even graphical languages. Functional Programming is unique where it is not a series of statements that form a program but a set of functions that turn into a series of evaluations that create the program.

Functional languages were the result of studies of formalizing notation of computation before modern computers had even been developed. The root of this work is by Alonzo Church and is known as lamda calculus. The calculus involved is the formal notation of how functions behave. [1] The use of functional languages is more accepted in academic institutions than in general programming use and is an example of an alternate to the more common program paradigms. Functional languages do provide a method to quickly prototype problems. For many years the functional language LISP was used in the study of AI.

The first actual imperative (FORTRAN) and functional (LISP) languages to run on actual computers were both implemented in the 1950's. As functional languages like LISP progressed some of the features similar to imperative programming have evolved into the language. This can be considered a split between functional and imperative languages. Imperative has been the mainstream choice of programming. Procedural and Object Oriented languages would develop from the imperative paradigm.


Mathematical Programming Language

Functional languages are generally very concise and bounded by parenthesis, similar to an algebraic formula. Each set of parenthesis is a function that will return a value into the function it is part of. The functional programming paradigm has roots in mathematical studies of computing and uses formatting similar to the formal descriptions of functions. An example using a simple algebraic formula x = a + b translated into functional language using LISP would result in (+ 2 3) where a, b are represented by 2, 3 and the return of x is 5. In this example, and other examples, LISP uses prefix notation versus traditional infix notation. The translation of the simple addition example into a more formal function and then to LISP.

x = a + b
f(x) = a + b
f(a + b)
(+ a b) where a,b are replaced by valid types
>(+ 2 3)

An important concept to expand the capability of a functional language is the values in a function can be functions or even functions of functions. LISP also supports lists as input which will not be detailed here but can be seen in the programming section below. The use of a function as a value in another function is known as composite functions.

x = a + (b - c)
f(x) = a + g(y)
where g(y) = b - c
f(a + (b - c)) where a,b,c are replaced by valid types
>(+ 2 (- 3 4))

To use a function on the return of the same function a function needs to be defined in the example using LISP. The function can then operate on a result it returns. In the example below 2 will be squared returning 4 to square(x) and then return 16.

In LISP if the following function is defined: (defun square(x) (* x x))
>(square (square 2))

A composite function can also be created.

f(x) = x * 3
g(x) = x - 1
g(f(x)) = ( f(x) - 1 )
If x is 2 the composite function in LISP would be:  
>( - ( * 2 3 ) 1 )

In LISP functions that are defined may use a single input or multiple inputs and can be represented as a function with multiple inputs.

f(x,y) = (x * x) + y
In LISP if the following function is defined: (defun func(x y) (+ (* x x) y))
>(func 2 1)

Difference From Imperative Languages

One major advantage of the simplest concepts of an imperative language over functional is the visible flow of the instructions in the code. Disregarding the states of variables and the program is the concept of a "recipe" which can be seen in the code to understand the solution of the problem. Functional programming, especially in its purest form, does not allow iteration, and therefore results in the use of recursion. Defined functions cannot do multiple actions except with conditionals, which can be limited. The programming technique of functional programming requires all functions or evaluations to return into another layer of evaluations. An imperative language can make a list in order of execution to be performed whereas functional programming requires layers of nesting by parenthesis to order evaluation. An analogy is that an imperative program will operate like reading down a list of statements (like a recipe) where as a functional program will become an algebraic formula representing the program. The imperative flow will operate on and change data and the functional program will only use data as input and then return a result calculated from that data.

First Class Functions

Functional languages have functions that are known as first class functions. The concept of a first class function is that for the same input to the function, it will return the same result every time it is called. In imperative programs and its derivatives, this is not always the case since stored data that could be used when a function is called may have changed. That is because imperative data is global, while functional programming data is not.


Recursion is possible in functional languages and this is often the method used for iteration. Early functional languages did not include the typical iteration and looping statements seen in many of the imperative program languages at the time. The example below can be seen using LISP to calculate a factorial given an input value.

( defun fact (n)
  ( cond 
    ( (equal n 0) 1 )
    (T ( * n (fact (- n 1)) ) ) 

A Partial Functional Language List

Some common functional languages are:

  • LISP: First functional language. Started as purely functional language, but soon acquired some important imperative features that increased its execution efficiency.
  • ML: A strongly typed functional language with more conventional syntax than LISP.
  • HASKELL: Haskell is partially based on ML but is a purely functional language.
  • APL: An early functional language developed in 1960. One unique feature is the symbols used in the language.
  • R: An an open source programming language for statistics. It is considered a functional language and is a common language in use today for data analysis.

LISP Programming

LISP is an acronym for "LISt Processing language" - so named because the list is one of the primary data structures in the language. Symbolic AI regards symbolic lists as being a key part of the way intelligent beings and systems actually store and manipulate information.


Lisp was invented by Artificial Intelligence (AI) pioneer John Mc Carthy in the late 1950s. McCarthy published its design in a paper in Communications of the ACM in 1960, entitled "Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I" (interesting that "Part II" was never published). [2] LISP was intended as a mathematical formalism for reasoning about the use of recursion equations as a model for computation. Of the computer languages that are still in widespread use today, only Fortran is older.

The Lisp family of languages has evolved with the field of computer science, both by putting the best ideas from the field into practical use, and by contributing many such ideas. The association of Lisp with research, however, has not always been beneficial. Lisp has always been among the main tools of AI since the beginning. When the commercial AI market failed to deliver on its promises, Lisp was blamed as a scapegoat. In the late 1980s, many companies abandoned Lisp in favor of other languages, starting the so called "AI winter". Although Lisp survived the crisis, some of the resulting prejudice and lack of information is still present in the computing field.

With growing popularity of LISP, many dialects were developed and were being used by LISP users by 1980's. The LISP community started a consolidation effort to design the Common Lisp dialect, which became the standard and commercial version of LISP.

Lisp in Artificial Intelligence

Lisp WAS used in AI until the end of the 1980s. In the 80s, though, Common Lisp was oversold to the business world as the "AI language"; the backlash forced most AI programmers to C++ for a few years.

1.Lisp is an excellent prototyping tool. It was the best for a very long time. Lisp is still great at tackling a problem you don't know how to solve yet. That description characterises AI perfectly.

2.Lisp supports symbolic programming well. Old AI was also symbolic. It was also unique in this regard for a long time.

3.Lisp is very powerful. The code/data distinction is weaker so it feels more extensible than other languages because your functions and macros look like the built-in stuff.

LISP, the first Functional Language

The oldest and most widely used functional language is Lisp.The functional programming paradigm, which is based on mathematical functions, is the design basis for one of the most important non-imperative styles of languages. This style of programming is supported by functional, or applicative, programming languages. Lisp began as a purely functional language, but it soon acquired some important imperative features that increased its execution efficiency. COMMON Lisp is an amalgam of several early 1980’s dialects of Lisp

LISP data types and objects

LISP has two categories of data objects:


An atom is a word or a number or the pair of parentheses "()" which we will call "NIL". So, by that description, all of the following are atoms:


In fact, there are a few more things that we can use as atoms also. The rules for creating atoms are, to be exact, as follows.

  • An atom can be any number the computer understands. This is called a numeric atom. These are integers like: 145, -15, 0, etc., or floating point numbers (ones with fractional parts) like: 1.4, -56.3, etc.
  • A non-numeric atom can be any name made up of letters and/or numbers. There is no limit on the length of this. The only restriction is that the first character must be a letter, not a number. This is called an alphanumeric atom.
  • The form of NIL "()" can be an atom.
  • Alphanumeric atoms can have some funny characters in them [such as "*" and "+"] but special Lisp characters cannot be used in atom names. This should be clear by now. The characters "(", ")", and "'", would simply confuse Lisp if you tried to use them in atom names. In general, we avoid using anything other than the letters "A" through "Z" and the numbers "0" through "9" in atom names.
  • Indivisible things like 27, 3.14 and + which have obvious meaning, as well as things like Foo and B27 that are called atoms.
  • Atoms like 27 and 3.14 are called numeric atoms and atoms like Foo and B27 are called symbolic atoms.


A list consist of a left parenthesis, followed by zero or more atoms or lists, followed by a right parenthesis.

When working with numbers, like 2 and 3, Lisp makes it easy to work with a group of several items, called a list. To specify a list of items you enclose the items in brackets. For example, the list of two-digit squares is:

(16 25 36 49 64 81)

A list containing no items is called the empty list. You can write it as:


but it is also called nil.

In fact we can ask the Lisp to evaluate a list:

(+ 2 3 4)

This was a list of four items: the symbol +, and the numbers 2, 3, and 4. When Lisp evaluates a list it treats the first item as the name of a procedure, and the remaining items as the arguments to the expression.

The output is ,


This illustrates one of the remarkable features of Lisp - Lisp programs and Lisp data are both expressed in the same way, as lists.

LISP Interpreter and the Polish notation

(function_name argument1 argument2 ... argument)

(+ 2 2) -> returns 4

(+ 2 4 6 8 10) -> returns 30

Common Functions

Assignment Set (remind readers to quote arguments with ' to prevent evaluation)

The set function takes two arguments and sets the symbol of the second to the symbol of the first argument. The second argument could be a list of Atoms and the whole list will be set to the symbol of the first argument. This is much like setting and initializing variables in other programming languages (int c = 2;). Both arguments need to be single quoted so that the first argument is not evaluated as a function. The setq function can be used and the single quote for the first argument can be dropped because the q on the end of set signifies quote.

(set ‘k ‘(a b c d e))
(setq k ‘(a b c d e))
(print k) returns (a b c d e)

Math functions: +, -, *, /

The grammatical structure that is used to perform mathematical computations in Lisp is a bit different then in a normal mathematics problem. In a mathematical problem we say “2 plus 4”. In Lisp we call the math operation first then the two arguments, so the problem is stated “Add(+) 2 and 4, Subtract(-) 2 from 4, Multiply(*) 2 and 4, or Divide(/) 2 by 4”.

 Mathematically: 2 + 4 = 6, 2 - 4 = 2, 2 * 4 = 8, 2 / 4 = ½ 
 Lisp: (+ 2 4) returns (6)
       (- 2 4) returns (2)
       (* 2 4) returns (8)
       (/ 2 4) returns (½)

After the first operation argument there can be one or many arguments that will be evaluated from left to right. When adding or multiplying the order of the second through last arguments doesn’t matter, but be aware that, just like in mathematics, with subtraction and division the order the arguments are arranged in matters.

(+ 1 2 3 4 5) returns (15)
(- 1 2 3 4 5) returns (-13)
(- 5 4 3 2 1) returns (-5)

The following table shows all the arithmetic operators supported by LISP. Assume variable A holds 10 and variable B holds 20 then: Examples

Operator Description Example
+ Adds two operands (+AB) will give 30
_ Subtracts second operand from the first (- A B) will give -10
* Multiplies both operands (* A B) will give 200
/ Divides numerator by de-numerator (/ B A) will give 2
mod,rem Modulus Operator and remainder of after an integer division (mod B A )will give 0
incf Increments operator increases integer value by the second argument specified (incf A 3) will give 13
decf Decrements operator decreases integer value by the second argument specified (decf A 4) will give 9

List functions: list, cons, append, car, cdr

  • Cons : Cons takes an expression and a list and returns a new list whose first element is the expression and whose remaining elements are those of the old list:
  • Append : Combines the elements of all lists supplied as arguments.
  • List : List does not run things together like APPEND does.Instead,it makes a list out of its arguments. Each argument becomes an element of the new list.

Defining functions: defun

The defun function is used for programming defined functions.

(defun <function name> (<arg1> . . . <argn>)
	( <function body> )

Conditional Functions: cond, null

  • Cond - This function is like the IF statement in other languages and can take the form of an if-else-if statement. When Cond is called the first conditional statement will be evaluated and if true then the next part will be evaluated and so on to the last Atom which then becomes the returned value. If the first conditional statement is false the second conditional statement will be evaluated and so on until a conditional statement tests true. In the last conditional statement a T can be used to force TRUE condition and have a value returned.
  • Null - This is used to evaluate an Atom to see if it have a value and returns either T (True) or NIL (False). Used many time as the first statement in a cond function to see if the Atom is not NIL and can be run through the conditional statements. (NULL X) is TRUE if X is NIL.
       ( <conditional 1> <function call or return value 1> )
       ( <conditional 2> <function call or return value 2> )
       ( <conditional n> <function call or return value n> )
       ( T               <function call or return value for default case> )

Recursive functions: differentiate recursive from iterative

Recursion in Lisp - Is the ability of a function to call itself from within itself. This condition then repeats until the call to itself is NIL.

Example  palindrome2 () 
(defun palindrome2 ()
    (set 'k '(a b c d))
    (append k (cdr (myReverse k)))
(defun myReverse (k)
        ((NULL k) k)
        (T (append (myReverse (cdr k)) (list (car k))))
Example Fibonacci () 
(defun fib (n)
        ((= n 0) 0); if 0 by definition it's 0
        ((= n 1) 1); if 1 by definition it's 1
        (T (+ (fib (- n 1)) (fib (- n 2))) ); if > 1 then add two previous values


A quick summary of the chapter should go here

Key Terms

LISP: LISt Processing.

Atoms: In the original LISP there were two fundamental data types: atoms and lists. A list was a finite ordered sequence of elements, where each element is in itself either an atom or a list, and an atom was a number or a symbol. A symbol was essentially a unique named item, written as an alphanumeric string in source code, and used either as a variable name or as a data item in symbolic processing. For example, the list (FOO (BAR 1) 2) contains three elements: the symbol FOO, the list (BAR 1), and the number 2.

The essential difference between atoms and lists was that atoms were immutable and unique. Two atoms that appeared in different places in source code but were written in exactly the same way represented the same object,[citation needed] whereas each list was a separate object that could be altered independently of other lists and could be distinguished from other lists by comparison operators.

As more data types were introduced in later Lisp dialects, and programming styles evolved, the concept of an atom lost importance.

Car/cdr: In computer programming, car /ˈkɑr/ and cdr (/ˈkʌdər/ or /ˈkʊdər/) are primitive operations on cons cells (or "non-atomic S-expressions") introduced in the Lisp programming language. A cons cell is composed of two pointers; the car operation extracts the first pointer, and the cdr operation extracts the second.

Thus, the expression (car (cons x y)) evaluates to x, and (cdr (cons x y)) evaluates to y.

Cond - This function is like the IF statement in other languages and can take the form of an if-else-if statement. When Cond is called the first conditional statement will be evaluated and if true then the next part will be evaluated and so on to the last Atom which then becomes the returned value. If the first conditional statement is false the second conditional statement will be evaluated and so on until a conditional statement tests true. In the last conditional statement a T can be used to force TRUE condition and have a value returned.

Lists: A Lisp list is written with its elements separated by whitespace, and surrounded by parentheses. For example, (1 2 foo) is a list whose elements are three atoms: the values 1, 2, and foo. These values are implicitly typed: they are respectively two integers and a Lisp-specific data type called a "symbolic atom", and do not have to be declared as such.

The empty list () is also represented as the special atom nil. This is the only entity in Lisp which is both an atom and a list.

Expressions are written as lists, using prefix notation. The first element in the list is the name of a form, i.e., a function, operator, macro, or "special operator" (see below). The remainder of the list are the arguments. For example, the function list returns its arguments as a list, so the expression

(list '1 '2 'foo)

evaluates to the list (1 2 foo). The "quote" before the arguments in the preceding example is a "special operator" which prevents the quoted arguments from being evaluated (not strictly necessary for the numbers, since 1 evaluates to 1, etc.). Any unquoted expressions are recursively evaluated before the enclosing expression is evaluated. For example,

(list 1 2 (list 3 4))

evaluates to the list (1 2 (3 4)). Note that the third argument is a list; lists can be nested.

Recursion (Recursive Functions):

Null - This is used to evaluate an Atom to see if it have a value and returns either T (True) or NIL (False). Used many time as the first statement in a cond function to see if the Atom is not NIL and can be run through the conditional statements. (NULL X) is TRUE if X is NIL.

Symbolic expressions (S-expressions): In computing, s-expressions, sexprs or sexps (for "symbolic expression") are a notation for nested list (tree-structured) data, invented for and popularized by the programming language Lisp, which uses them for source code as well as data. In the usual parenthesized syntax of Lisp, an s-expression is classically defined[1] inductively as

   an atom, or
   an expression of the form (x . y) where x and y are s-expressions.

The second, recursive part of the definition represents an ordered pair so that s-exprs are effectively binary trees.

The definition of an atom varies per context; in the original definition by John McCarthy,[1] it was assumed that there existed "an infinite set of distinguishable atomic symbols" represented as "strings of capital Latin letters and digits with single embedded blanks" (i.e., character string and numeric literals). Most modern sexpr notations in addition use an abbreviated notation to represent lists in s-expressions, so that

   (x y z)

stands for

   (x . (y . (z . NIL)))

where NIL is the special end-of-list symbol (written '() in Scheme).

In the Lisp family of programming languages, s-expressions are used to represent both source code and data. Other uses of S-expressions are in Lisp-derived languages such as DSSSL, and as mark-up in communications protocols like IMAP and John McCarthy's CBCL. The details of the syntax and supported data types vary in the different languages, but the most common feature among these languages is the use of S-expressions and prefix notation.

Lambda expressions:

...other key terms:

Problem Sets

Basics 1. Evaluate the following expressions:

(+ 2 2)

(- 4 2)

(* 5 2)

(/ 10 5)

(/ 11 2)

(+ 1 2 3 4 5 6 7 8 9)

(* 1 2 3 4 5)

(* (+ 2 3) (/ 24 6))

(/ (* (- 212 32) 5) 9)

2. Evaluate the following forms:

(car '(a b c))

(cdr '(m n o p))

(car '((a b) (c d))

(cdr '((a b) (c d))

(car (cdr (car (cdr '((a b) (c d) (e f))))))

(car (car (cdr (cdr '((a b) (c d) (e f))))))

(car (cdr (car '(cdr ((a b) (c d) (e f))))))

(car (cdr '(car (cdr ((a b) (c d) (e f))))))

(car '(cdr (car (cdr ((a b) (c d) (e f))))))

3. Using only CAR and CDR, try to pick the atom PEAR our of the following lists:

(apple orange pear grape)

((apple orange) (pear grape))

(((apple) (orange) (pear) (grape)))

(apple (orange) ((pear)) (((grape))))

((((apple))) ((orange)) (pear) grape)

((((apple) orange) pear) grape)

4. Understanding APPEND and LIST

First let's define two lists, ab-list and cd-list as follows:

(setq ab-list '(a b) cd-list '(c d))

(append ab-list cd-list)

(list ab-list cd-list)

(append ab-list ab-list)

(list ab-list ab-list)

(append 'ab-list ab-list)

(list 'ab-list ab-list)

(list (car ab-list) cd-list)

(append (car ab-list) cd-list)

5. Defining your own function:

    (defun double (num)
       (* num 2))
    (defun half (num)
       (/ num 2))
    (defun Celcius (temp)
       (/ (* (- 212 32) 5) 9))

6. Conditionals. Evaluate these expressions:

  (setq bmi 25)
  (cond ((> bmi 30) 'obesity)
        ((> bmi 25) 'overweight)
        ((> bmi 20) 'normal-weight)
        (t 'underweight))
  (setq distance 40)
  (cond ((> distance 40) 'very-long-commute)
        ((> distance 30) 'long-commute)
        ((> distance 20) 'average)
        ((> distance 10) 'short-commute)
        (t 'no-commute))

7. Recursion

  (defun (factorial n) 
     (cond ((= n 0) 1)
           (t (* n (factorial (- n 1))))))


1. Paul Hudak, "The Conception, Evolution, and Application of Functional Programming Languages", Yale University, Department of Computer Science, March 1989, Retrieved from www.dbnet.ece.ntua.gr/~adamo/languages/books/p359-hudak.pdf

2. en.wikipedia.org/wiki/History_of_the_Scheme_programming_language

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