Scheme: changing recursion to tail recursion - recursion

I'm unsure of how to turn count-forwards into a tail-recursive program. It takes a non-negative number, n, and returns the list of integers from 0 to n (including n).
Edit: Okay, I finally got this one to work. The problem wasn't that my current program was recursive and I needed to make it tail-recursive- It was just plain wrong. The actual answer is really short and clean. So if anyone else is stuck on this and is also a total programming noob, here's a few hints that might help:
1) Your helper program is designed to keep track of the list so far.
2) Its base case is.. If x = 0.. what do you do? add 0 onto.. something.
3) Recur on x - 1, and then add x onto your list so far.
4) When you get to your actual program, count-forwards, all you need is the helper. But remember that it takes two arguments!

The only recursive function here is list-reverse. It is tail-recursive, because the call to itself is the last operation in the function body.
Your function for generating a nondecreasing sequence from zero to m, which contains the successive results of adding 1 to the previous element, would look something like:
(define (my-reverse lst)
(define (rev-do xs ys)
(if (empty? xs)
ys
(rev-do (cdr xs) (cons (car xs) ys))))
(rev-do lst empty))
(define (seq m n)
(seq-do m n (list m)))
(define (seq-do m n xs)
(if (= m n)
(my-reverse xs)
(let ((next (add1 m)))
(seq-do next n (cons next xs)))))
(define (seq-from-zero m)
(seq 0 m))
Test:
> (seq-from-zero 10)
(0 1 2 3 4 5 6 7 8 9 10)
seq-do is a general function for generating nondecreasing sequences from m to n; it is tail-recursive, because the last operation is the call to itself.
I've also implemented reverse from scratch, so that you can use it in your homework problems.

Related

How to assure a function is tail-recursive? [duplicate]

I'm studying for a Christmas test and doing some sample exam questions, I've come across this one that has me a bit stumped
I can do regular recursion fine, but I can't wrap my head around how to write the same thing using tail recursion.
Regular version:
(define (factorial X)
(cond
((eqv? X 1) 1)
((number? X)(* X (factorial (- X 1))))))
For a function to be tail recursive, there must be nothing to do after the function returns except return its value. That is, the last thing that happens in the recursive step is the call to the function itself. This is generally achieved by using an accumulator parameter for keeping track of the answer:
(define (factorial x acc)
(if (zero? x)
acc
(factorial (sub1 x) (* x acc))))
The above procedure will be initially called with 1 as accumulator, like this:
(factorial 10 1)
=> 3628800
Notice that the accumulated value gets returned when the base case is reached, and that the acc parameter gets updated at each point in the recursive call. I had to add one extra parameter to the procedure, but this can be avoided by defining an inner procedure or a named let, for example:
(define (factorial x)
(let loop ((x x)
(acc 1))
(if (zero? x)
acc
(loop (sub1 x) (* x acc)))))

how can i call a function that takes an argument in racket?

I am still new in racket language.
I am implementing a switch case in racket but it is not working.
So, I shift into using the equal and condition. I want to know how can i call a function that takes input. for example: factorial(n) function
I want to call it in :
(if (= c 1) (factorial (n))
There are two syntax problems with this snippet:
(if (= c 1) (factorial (n)))
For starters, an if expression in Racket needs three parts:
(if <condition> <consequent> <alternative>)
The first thing to fix would be to provide an expression that will be executed when c equals 1, and another that will run if c is not equal to 1. Say, something like this:
(if (= c 1) 1 (factorial (n)))
Now the second problem: in Scheme, when you surround a symbol with parentheses it means that you're trying to execute a function. So if you write (n), the interpreter believes that n is a function with no arguments and that you're trying to call it. To fix this, simply remove the () around n:
(if (= c 1) 1 (factorial n))
Now that the syntax problems are out of the way, let's examine the logic. In Scheme, we normally use recursion to express solutions, but a recursion has to advance at some point, so it will eventually end. If you keep passing the same parameter to the recursion, without modifying it, you'll get caught in an infinite loop. Here's the proper way to write a recursive factorial procedure:
(define (factorial n)
(if (<= n 0) ; base case: if n <= 0
1 ; then return 1
(* n (factorial (- n 1))))) ; otherwise multiply and advance recursion
Notice how we decrement n at each step, to make sure that it will eventually reach zero, ending the recursion. Once you get comfortable with this solution, we can think of making it better. Read about tail recursion, see how the compiler will optimize our loops as long as we write them in such a way that the last thing done on each execution path is the recursive call, with nothing left to do after it. For instance, the previous code can be written more efficiently as follows, and see how we pass the accumulated answer in a parameter:
(define (factorial n)
(let loop ([n n] [acc 1])
(if (<= n 0)
acc
(loop (- n 1) (* n acc)))))
UPDATE
After taking a look at the comments, I see that you want to implement a switchcase procedure. Once again, there are problems with the way you're declaring functions. This is wrong:
(define fact(x)
The correct way is this:
(define (fact x)
And for actually implementing switchcase, it's possible to use nested ifs as you attempted, but that's not the best way. Learn how to use the cond expression or the case expression, either one will make your solution simpler. And anyway you have to provide an additional condition, in case c is neither 1 nor 2. Also, you're confounding the parameter name - is it c or x? With all the recommendations in place, here's how your code should look:
(define (switchcase c)
(cond ((= c 1) (fact c))
((= c 2) (triple c))
(else (error "unknown value" c))))
In racket-lang, conditionals with if has syntax:
(if <expr> <expr> <expr>)
So in your case, you have to provide another <expr>.
(define (factorial n)
(if (= n 1) 1 (* n (factorial (- n 1)))))
;^exp ^exp ^exp
(factorial 3)
The results would be 6
Update:
(define (factorial n)
(if (= n 1) 1 (* n (factorial (- n 1)))))
(define (triple x)
(* 3 x))
(define (switchcase c)
(if (= c 1)
(factorial c)
(if(= c 2)
(triple c) "c is not 1 or 2")))
(switchcase 2)
If you want something a lot closer to a switch case given you can return procedures.
(define (switch input cases)
(let ((lookup (assoc input cases)))
(if lookup
(cdr lookup)
(error "Undefined case on " input " in " cases))))
(define (this-switch c)
(let ((cases (list (cons 1 triple)
(cons 2 factorial))))
((switch c cases) c)))

Tail recursive functions in Scheme

I'm studying for a Christmas test and doing some sample exam questions, I've come across this one that has me a bit stumped
I can do regular recursion fine, but I can't wrap my head around how to write the same thing using tail recursion.
Regular version:
(define (factorial X)
(cond
((eqv? X 1) 1)
((number? X)(* X (factorial (- X 1))))))
For a function to be tail recursive, there must be nothing to do after the function returns except return its value. That is, the last thing that happens in the recursive step is the call to the function itself. This is generally achieved by using an accumulator parameter for keeping track of the answer:
(define (factorial x acc)
(if (zero? x)
acc
(factorial (sub1 x) (* x acc))))
The above procedure will be initially called with 1 as accumulator, like this:
(factorial 10 1)
=> 3628800
Notice that the accumulated value gets returned when the base case is reached, and that the acc parameter gets updated at each point in the recursive call. I had to add one extra parameter to the procedure, but this can be avoided by defining an inner procedure or a named let, for example:
(define (factorial x)
(let loop ((x x)
(acc 1))
(if (zero? x)
acc
(loop (sub1 x) (* x acc)))))

Tail Recursive counting function in Scheme

The function is supposed to be tail-recursive and count from 1 to the specified number. I think I'm fairly close. Here's what I have:
(define (countup l)
(if (= 1 l)
(list l)
(list
(countup (- l 1))
l
)
)
)
However, this obviously returns a list with nested lists. I've attempted to use the append function instead of the second list to no avail. Any guidance?
Here's an incorrect solution:
(define (countup n)
(define (help i)
(if (<= i n)
(cons i (help (+ i 1)))
'()))
(help 1))
This solution:
uses a helper function
recurses over the numbers from 1 to n, cons-ing them onto an ever-growing list
Why is this wrong? It's not really tail-recursive, because it creates a big long line of cons calls which can't be evaluated immediately. This would cause a stack overflow for large enough values of n.
Here's a better way to approach this problem:
(define (countup n)
(define (help i nums)
(if (> i 0)
(help (- i 1)
(cons i nums))
nums)))
(help n '()))
Things to note:
this solution is better because the calls to cons can be evaluated immediately, so this function is a candidate for tail-recursion optimization (TCO), in which case stack space won't be a problem.
help recurses over the numbers backwards, thus avoiding the need to use append, which can be quite expensive
You should use an auxiliar function for implementing a tail-recursive solution for this problem (a "loop" function), and use an extra parameter for accumulating the answer. Something like this:
(define (countup n)
(loop n '()))
(define (loop i acc)
(if (zero? i)
acc
(loop (sub1 i) (cons i acc))))
Alternatively, you could use a named let. Either way, the solution is tail-recursive and a parameter is used for accumulating values, notice that the recursion advances backwards, starting at n and counting back to 0, consing each value in turn at the beginning of the list:
(define (countup n)
(let loop ((i n)
(acc '()))
(if (zero? i)
acc
(loop (sub1 i) (cons i acc)))))
Here a working version of your code that returns a list in the proper order (I replaced l by n):
(define (countup n)
(if (= 1 n)
(list n)
(append (countup (- n 1)) (list n))))
Sadly, there is a problem with this piece of code: it is not tail-recursive. The reason is that the recursive call to countup is not in a tail position. It is not in tail position because I'm doing an append of the result of (countup (- l 1)), so the tail call is append (or list when n = 1) and not countup. This means this piece of code is a normal recusrive function but to a tail-recursive function.
Check this link from Wikipedia for a better example on why it is not tail-recusrive.
To make it tail-recursive, you would need to have an accumulator responsible of accumulating the counted values. This way, you would be able to put the recursive function call in a tail position. See the difference in the link I gave you.
Don't hesitate to reply if you need further details.
Assuming this is for a learning exercise and you want this kind of behaviour:
(countup 5) => (list 1 2 3 4 5)
Here's a hint - in a tail-recursive function, the call in tail position should be to itself (unless it is the edge case).
Since countup doesn't take a list of numbers, you will need an accumulator function that takes a number and a list, and returns a list.
Here is a template:
;; countup : number -> (listof number)
(define (countup l)
;; countup-acc : number, (listof number) -> (listof number)
(define (countup-acc c ls)
(if ...
...
(countup-acc ... ...)))
(countup-acc l null))
In the inner call to countup-acc, you will need to alter the argument that is checked for in the edge case to get it closer to that edge case, and you will need to alter the other argument to get it closer to what you want to return in the end.

How to improve this piece of code?

My solution to exercise 1.11 of SICP is:
(define (f n)
(if (< n 3)
n
(+ (f (- n 1)) (* 2 (f (- n 2))) (* 3 (f (- n 3))))
))
As expected, a evaluation such as (f 100) takes a long time. I was wondering if there was a way to improve this code (without foregoing the recursion), and/or take advantage of multi-core box. I am using 'mit-scheme'.
The exercise tells you to write two functions, one that computes f "by means of a recursive process", and another that computes f "by means of an iterative process". You did the recursive one. Since this function is very similar to the fib function given in the examples of the section you linked to, you should be able to figure this out by looking at the recursive and iterative examples of the fib function:
; Recursive
(define (fib n)
(cond ((= n 0) 0)
((= n 1) 1)
(else (+ (fib (- n 1))
(fib (- n 2))))))
; Iterative
(define (fib n)
(fib-iter 1 0 n))
(define (fib-iter a b count)
(if (= count 0)
b
(fib-iter (+ a b) a (- count 1))))
In this case you would define an f-iter function which would take a, b, and c arguments as well as a count argument.
Here is the f-iter function. Notice the similarity to fib-iter:
(define (f-iter a b c count)
(if (= count 0)
c
(f-iter (+ a (* 2 b) (* 3 c)) a b (- count 1))))
And through a little trial and error, I found that a, b, and c should be initialized to 2, 1, and 0 respectively, which also follows the pattern of the fib function initializing a and b to 1 and 0. So f looks like this:
(define (f n)
(f-iter 2 1 0 n))
Note: f-iter is still a recursive function but because of the way Scheme works, it runs as an iterative process and runs in O(n) time and O(1) space, unlike your code which is not only a recursive function but a recursive process. I believe this is what the author of Exercise 1.1 was looking for.
I'm not sure how best to code it in Scheme, but a common technique to improve speed on something like this would be to use memoization. In a nutshell, the idea is to cache the result of f(p) (possibly for every p seen, or possibly the last n values) so that next time you call f(p), the saved result is returned, rather than being recalculated. In general, the cache would be a map from a tuple (representing the input arguments) to the return type.
Well, if you ask me, think like a mathematician. I can't read scheme, but if you're coding a Fibonacci function, instead of defining it recursively, solve the recurrence and define it with a closed form. For the Fibonacci sequence, the closed form can be found here for example. That'll be MUCH faster.
edit: oops, didn't see that you said forgoing getting rid of the recursion. In that case, your options are much more limited.
See this article for a good tutorial on developing a fast Fibonacci function with functional programming. It uses Common LISP, which is slightly different from Scheme in some aspects, but you should be able to get by with it. Your implementation is equivalent to the bogo-fig function near the top of the file.
To put it another way:
To get tail recursion, the recursive call has to be the very last thing the procedure does.
Your recursive calls are embedded within the * and + expressions, so they are not tail calls (since the * and + are evaluated after the recursive call.)
Jeremy Ruten's version of f-iter is tail-recursive rather than iterative (i.e. it looks like a recursive procedure but is as efficient as the iterative equivalent.)
However you can make the iteration explicit:
(define (f n)
(let iter
((a 2) (b 1) (c 0) (count n))
(if (<= count 0)
c
(iter (+ a (* 2 b) (* 3 c)) a b (- count 1)))))
or
(define (f n)
(do
((a 2 (+ a (* 2 b) (* 3 c)))
(b 1 a)
(c 0 b)
(count n (- count 1)))
((<= count 0) c)))
That particular exercise can be solved by using tail recursion - instead of waiting for each recursive call to return (as is the case in the straightforward solution you present), you can accumulate the answer in a parameter, in such a way that the recursion behaves exactly the same as an iteration in terms of the space it consumes. For instance:
(define (f n)
(define (iter a b c count)
(if (zero? count)
c
(iter (+ a (* 2 b) (* 3 c))
a
b
(- count 1))))
(if (< n 3)
n
(iter 2 1 0 n)))

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