Some students do not read documentation or instructions. (Present company excluded, of course.) As a result, they write functions that already exist, sometimes under a different name. That's not even always a bad thing... Perhaps it's better to use your time practicing than poking around documentation.
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Write a Racket function (nth lst n), where lst is a list and n is a non-negative integer. nth returns the symbol in position n of lst. For example:
> (nth '(a b c) 2) 'c > (nth '(d c b a z) 1) 'c > (nth (range 1 1000) 41) 42 > (nth '(d c b a z) 10) nth: no such position
Make the position 0-based. If n is too big for the list, return an error message as a string.
Check out a candidate solution in this source file. This is a fine example of using structural recursion to process an inductively-defined datatype. As we have seen, a Racket list can be defined inductively as:
<list> ::= () | (<any> . <list>)Racket even has a built-in predicate for the "any" datatype, named any/c. We don't need it here, because we don't operate on the items in the list; we only return one of them.
Note a few things... First, it is probably simpler if we think of the inductive datatype being processed in this problem as the list, not the number. That way, the number comes along for the ride, getting decremented on each call. If we think of processing the number, we end up nesting the second if expression in an odd way.
Second, we do not need an interface procedure to solve this problem. Unlike annotate last time, this function requires that users pass an integer argument. We can use it to simulate a loop by counting down to zero in parallel with walking down the list.
Third, if the second argument were a symbol and we needed to return the position of the first occurrence, then we would need an interface procedure. That is Problem 5 on Homework 4!
nth is an implementation of Racket's primitive list-ref function. You can find many other functions for working with lists in the Racket docs. Most of them are also great exercises for practicing your recursive programming skills!
My solution uses Racket's primitive error function. Feel free to use it whenever a function has an error case. (Notice that we can test our error cases, using another test feature of Rackunit.)
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Writing recursive functions well and confidently requires you to know several techniques, just as writing loops does. Last session, we explored the basic technique for writing recursive programs, the technique on which we base all of our recursive functions: structural recursion. With this technique, we mimic the structure of an inductive data specification in the code that processes the data.
We then introduced a second technique, the interface procedure, that hides implementation detail and allows us to preserve the argument signature specified for a function. Interface procedures are necessary whenever we find that we need a piece of data on each recursive call that is not provided by the original caller of the function.
This is a common occurrence in Racket. We encounter it frequently when processing vectors, which require positional access to values.
This session continues our discussion of recursive programming by introducing two new techniques: mutual recursion and program derivation. These techniques also help us to do structural recursion in the face of specific circumstances that we commonly encounter.
Last session, we defined two functions, remove-first and remove, over lists of symbols. List of symbols is the data type on which they operate, and we had an inductive definition for the type that guided our work. Today, let's consider a more complex data structure, one that will be of great use to us when we write programs to process languages: the s-list. The difference between a list of symbols and an s-list is that the elements of the list can themselves be s-lists.
Here is the BNF notation for an s-list:
<s-list> ::= () | (<symbol-expression> . <s-list>) <symbol-expression> ::= <symbol> | <s-list>
And here are some examples:
() (()) (a) ((a) b) (a b c) (a (b) c) (a b c d) (if (zero? n) zero (/ total n)) (a b c d e f g h) (cons (foo (car x)) (foo-cdr (cdr x)))
The items on the left are lists of symbols, but they are also s-lists. A symbol-expression can be a symbol, or an s-list.
Let's define a function, subst, that substitutes one symbol for another anywhere in an s-list. You can think of this as like a global "search and replace" operation. For example, when applied to a program, subst can serve as the foundation of an operation for renaming variables -- a common refactoring that all programmers do.
This function takes three arguments: the new symbol, the old symbol, and an s-list to operate on:
> (subst 'd 'b '(a b c a b c d)) (a d c a d c d) > (subst 'a 'b '((a b) (((b g r) (f r)) c (d e)) b)) ((a a) (((a g r) (f r)) c (d e)) a)
Following the principle of structural recursion, the structure of subst should follow the structure of the BNF specification for an s-list:
(define subst (lambda (new old slist) (if (null? slist) ;; handle the empty list ;; handle a pair containing a symbol-expression )))
If slist is empty, there are nothing occurrences of old to substitute, and the answer is the empty list.
(define subst (lambda (new old slist) (if (null? slist) '() ;; handle a pair containing a symbol-expression )))
The second arm of our BNF definition defines a case where slist is a pair with the form (<symbol-expression> . <s-list>). The result of subst will be the result of substituting new for old in both parts, the <symbol-expression> and the <s-list>.
The first element of the pair is a symbol-expression. Note, however, that symbol-expression is also defined in terms of a choice. Our natural inclination might be to implement this choice with a conditional expression. There are two alternatives: the first element is a symbol, or it is an s-list.
(define subst (lambda (new old slist) (if (null? slist) '() (if (symbol? (first slist)) ;; handle a symbol in the first, then the slist in the rest ;; handle an slist in the first, then the slist in the rest ))))
We have to return a list with the same structure as our input, so in both cases we cons the result from the first into the result from the rest.
(define subst (lambda (new old slist) (if (null? slist) '() (if (symbol? (first slist)) (cons ;; handle symbol in first ;; handle slist in rest) (cons ;; handle slist in first ;; handle slist in rest) ))))
If it is a symbol, we must determine whether or not to replace it with new. We replace the symbol if it is equal to old, and otherwise we leave it alone:
(define subst (lambda (new old slist) (if (null? slist) '() (if (symbol? (first slist)) (if (eq? (first slist) old) (cons new ;; handle the slist in the rest ) (cons (first slist) ;; handle the slist in the rest ) ;; handle an slist in the first, then the slist in the rest ))))
In both of these cases, we need to substitute new for old in the rest of the list. The rest is an s-list, so we can use subst to compute that part of our result.
(define subst (lambda (new old slist) (if (null? slist) '() (if (symbol? (first slist)) (if (eq? (first slist) old) (cons new (subst new old (rest slist))) (cons (first slist) (subst new old (rest slist))) ) ;; handle an slist in the first, then the slist in the rest ))))
The only thing left to do is to decide what to do when the first member of slist is not a symbol. In that case, it is an s-list. We are in luck. We already have a fucntion for substituting symbols in s-lists. It is the function that we are writing, subst! So, we can:
(define subst (lambda (new old slist) (if (null? slist) '() (if (symbol? (first slist)) (if (eq? (first slist) old) (cons new (subst new old (rest slist))) (cons (first slist) (subst new old (rest slist))) ) (cons (subst new old (first slist)) (subst new old (rest slist)))))))
And we are done, or at least with we have a working solution. Our basic structural recursion technique has served us well.
Programming Aside: Notice how the indentation of this code makes the control structures we are using as clear as possible. Whenever you write a program -- especially in a language like Racket (with a uniform syntax (and so (many) function calls!)) -- you should strive to write code that tells us how to read itself.
Our function works but, if we are honest with ourselves, we must admit that it has a couple of weaknesses.
First, we have repeated the expression (subst new old (rest slist)) three times, including twice in the same arm of the main if expression. We know that repeated code can cause all sorts of problems in maintenance. But having to write these expressions separately also makes it hard for us to write the function in the first place. A mistake, even a typo, in any of the expressions will break our function. Besides, all the repetition makes the code harder to read.
Second, it is not really faithful to the structure suggested by the BNF. Look at the definition of an s-list again:
<s-list> ::= () | (<symbol-expression> . <s-list>) <symbol-expression> ::= <symbol> | <s-list>
Structural recursion tells us that the structure of our code should reflect the structure of the data. Our code does not. There are two BNF expressions in the data definition, but we have written only one function!
The second weakness causes the first. By not following the data structure, we have created extra cases to solve, which requires us to duplicate code.
If you look back at the step-by-step evolution of our function, you will see a clue hinting at this second weakness. We had to leave ourselves detailed notes using comments so that we did not lose our place as we solved small parts of the problem. Those comments are a sign that we are managing a lot of complexity in our heads. But the data type we are processing is not that complex!
My running commentary does more than give us a clue about when we went off track. It tells us exactly where:
The first element of the pair is a symbol-expression. Note, however, that symbol-expression is also defined in terms of a choice. Our natural inclination might be to implement this choice with a conditional expression. . ...
A better way to reflect the choice between kinds of symbol expression would be to follow the data definition. An s-list is defined in terms of symbol expression, and a symbol expression is defined in terms of s-list. We say that such data types are mutually inductive. We'd like for our code to show this relationship, too.
Patterns that show up in data should probably show up in the code that processes the data. (And in the languages we use to write the code...)
For our program structure to follow the pattern of the BNF, we must define a function for substituting symbols in s-lists, called subst, and a function for substituting symbols in symbol expressions, called, say, subst-symbol-expr. Because each data type is defined in terms of the other, these functions will call one another. This technique is called mutual recursion, because the recursion involves two functions that call one another, working together to create a solution.
To begin, let's suppose that subst-symbol-expr exists and works. The "else" clause of our main decision in subst becomes quite easy to write:
The definition of subst becomes:
(define subst (lambda (new old slist) (if (null? slist) '() (cons (subst-symbol-expr new old (first slist)) (subst new old (rest slist))) )))
Isn't that much clearer?
Now we have to write subst-symbol-expr. Using structural recursion, the definition of this function follows the BNF definition of the data type it processes, a symbol expression. The BNF lists two alternatives for a symbol expression: it is either a symbol, or it is an s-list. So:
(define subst-symbol-expr (lambda (new old symexp) (if (symbol? symexp) ;; handle a symbol ;; handle an slist )))
If the symbol expression is a symbol, then we decide whether to replace it with the new symbol:
(define subst-symbol-expr (lambda (new old symexp) (if (symbol? symexp) (if (eq? symexp old) new symexp) ;; handle an slist )))
If not, then it is an s-list. But we have already written a function that can make substitutions in an s-list: subst! Call it:
(define subst-symbol-expr (lambda (new old symexp) (if (symbol? symexp) (if (eq? symexp old) new symexp) (subst new old symexp))))
That's pretty clear, too.
Our solution now consists of two relatively small, relatively simple functions that work together to solve the problem.
What are the advantages of our new program?
Mutual recursion will be our technique of choice whenever we
have a multiple-part data definition.
Use mutual recursion to implement (count-occurrences s slist), which counts how many times the symbol s occurs in slist.
> (count-occurrences 'a '(a b c)) 1 > (count-occurrences 'a '(((a be) a ((si be a) be (a be))) (be g (a si be)))) 5
The first step is to examine the BNF:
<s-list> ::= () | (<symbol-expression> . <s-list>) <symbol-expression> ::= <symbol> | <s-list>
From the BNF, we expect to write two functions, one that counts the symbol in an s-list and one that counts the symbol in a symbol expression.
We start with the pattern suggested by the BNF for s-list:
(define count-occurrences (lambda (s slist) (if (null? slist) ...;; slist is empty ...;; slist is a pair )))
We can conclude without much effort that a symbol occurs in an empty list 0 times. In a non-empty list, the number of times it occurs is equal to the number of times it occurs in the first of the list plus the number of times it occurs in the rest of the list.
Because this is a mutually recursive specification and function, we will assume that a function named count-occurrences-sym-expr exists, so that we can use it to count the number of occurrences in the car of the pair:
(define count-occurrences (lambda (s slist) (if (null? slist) 0 (+ (count-occurrences-sym-expr s (first slist)) (count-occurrences s (rest slist))) )))
Now, we define count-occurrences-sym-expr. The BNF description for symbol expressions suggests the following pattern:
(define count-occurrences-sym-expr (lambda (s sym-expr) (if (symbol? sym-expr) ...;; sym-expr is a symbol ...;; sym-expr is an slist )))
If the symbol expression is a symbol, then we need to determine whether it is the symbol we're counting or not and return the appropriate value, 0 or 1. If it is an s-list, then we have a function for counting occurrences -- count-occurrences:
(define count-occurrences-sym-expr (lambda (s sym-expr) (if (symbol? sym-expr) (if (eq? s sym-expr) 1 0) ;; sym-expr is a symbol (count-occurrences s sym-expr) ))) ;; sym-expr is an slist
And we are done!
Our original definition of subst was somewhat confusing -- to read and to write. We just saw that following the BNF can make the program easier to program and easier to understand. This ease comes, however, at the cost of extra function calls.
How so? Notice that we now make two function calls each time the first of the s-list contains an s-list: one to subst-symbol-expr, and then a return call to subst. Such "double dispatch" can be expensive on a large dataset.
Sometimes, the run-time costs introduced by mutual recursion outweigh the program-time and read-time benefits of the separate functions. Can we modify our definition without losing too many of its benefits?
We can use Racket's substitution model to get back to a single function. Our solution currently looks like this:
(define subst (lambda (new old slist) (if (null? slist) '() (cons (subst-symbol-expr new old (first slist)) (subst new old (rest slist)))))) (define subst-symbol-expr (lambda (new old symexp) (if (symbol? symexp) (if (eq? symexp old) new symexp) (subst new old symexp))))
We can substitute the definition of subst-symbol-expr into subst, using the standard rules from the substitution model. This is exactly what the Racket interpreter will do at run-time. First, we substitute the lambda in place of the name:
(define subst (lambda (new old slist) (if (null? slist) '() (cons ( (lambda (new old symexp) ;; (if (symbol? symexp) ;; Here (if (eq? symexp old) ;; is new ;; the symexp) ;; first (subst new old se))) ;; substitution. new old (first slist)) (subst new old (rest slist))))))
Next, we replace the application of the lambda with the body of the lambda, substituting the arguments for the corresponding formal parameters: new for new, old for old, and (first slist) for symexp:
(define subst (lambda (new old slist) (if (null? slist) '() (cons (if (symbol? (first slist)) ;; (if (eq? (first slist) old) ;; Here is new ;; the second (first slist)) ;; substitution. (subst new old (first slist))) ;; (subst new old (rest slist))))))
The result is a single function that behaves exactly like the two original functions. After all, all we did was to derive by hand the same result that the Racket evaluator will produce. So, provided that we made no errors in our derivation, the resulting function has the same functionality. However, the new version is more efficient, because it eliminates the extra function calls. We hope that it is nearly as readable as the two-function version.
Take a closer look. The derived function is not like the single-function solution we wrote earlier. That function repeated the expression (subst new old (cdr slist)) several times, because we worked through the details of every possible case. Using mutual recursion followed by program derivation -- letting Racket's substitution model do some of the work for us -- results in a program with a single (subst new old (rest slist)).
We can do this in Racket because the if construct is an expression that returns a value, not a statement. In many languages, if is a statement and returns no value. A few, including Java and C++, have a "computed if" expression that may let us do something like this. In Java, a "computed if" is written as
<test> ? <then-value> : <else-value>
C++ has a concept that is similar to program derivation, the in-lining of member functions. The difference, though, is that its is implemented by the compiler. When we declare a class member function inline, the compiler tries to replace all calls to the function with equivalent code from the body of the function.
For example, we may well use an accessor method x() frequently when interacting with an object that has an x-coordinate. By declaring the x() method as inline, the compiler will replace the method call with the equivalent code from the body of the function.
This enables the programmer to eliminate the overhead of extra function calls at run time, without obscuring the readability and design of our class. Program derivation works like inlining, but it is a technique used by programmers to modify their code. (I can certainly imagine having a Racket compiler implementing program derivation automatically, thus saving the programmer the effort and risk of error!)
We will use the program derivation technique occasionally to simplify the result of mutual recursion, and any other technique that introduces unwanted function calls that create undesirable inefficiency at run-time -- but only when the cost of the extra function calls outweighs the benefits of separate functions.
Use program derivation to eliminate the count-occurrences-symbol-expr function. Do you like the result?