Working on a homework question asking to write a DFA-acceptor in Scheme. Alphabet: {0, 1} Start-state: {Q0} Final-state: {Q2}. String must have a 01 in the sequence to be accepted.
States:
Q0 on 1 transitions to Q1.
Q0 on 0 transitions to Q0.
Q1 on 1 transitions to Q2.
Q1 on 0 transitions to P.
Q2 on 0 and 1 transitions to Q1.
The teacher requested each state to be a function and to return a function that it transitions to. (Q0 1) returns Q1, etc. Code below is an attempt to get things running, before worrying about checking if 01 is in the string. Currently getting an error: "Q0: unbound identifier;" and am not sure why after doing some searching. Any pointers would be helpful. The question is for homework, so not looking for direct answers. Thank you!
#lang racket
(define DFA-trans '((Q0 x) (Q1 x) '((Q2 x)) (P x)))
(define x '(1 1 0 1 0))
(define P(null? 1))
(define Q2 (lambda(x)
(if (null? (car x))
#t
(if (equal? (car x) 0)
(Q2 (cdr x))
(if (equal? (car x) 1)
(Q2 (cdr x))
#t
)))))
(define Q1 (lambda(x)
(if (null? (car x))
#f
(if (equal? (car x) 0)
(P (cdr x))
(if (equal? (car x) 1)
(Q2 (cdr x))
#f
)))))
(define Q0 (lambda(x)
(if (null? (car x))
#f
(if (equal? (car x) 0)
(Q0 (cdr x))
(if (equal? (car x) 1)
(Q1 (cdr x))
#f
)))))
(define DFA(map eval DFA-trans))
(DFA)
Don't use EVAL for this.
The definitions of P, Q0, Q1, Q2 look good.
If we can define DFA directly, you can just delete DFA-trans.
Assuming Q0 is the start state, I think you can simply do this
(define DFA (lambda () (Q0 x)))
And consider using COND instead of nested IF.
Related
I'm working on this project in Scheme and these errors on these three particular methods have me very stuck.
Method #1:
; Returns the roots of the quadratic formula, given
; ax^2+bx+c=0. Return only real roots. The list will
; have 0, 1, or 2 roots. The list of roots should be
; sorted in ascending order.
; a is guaranteed to be non-zero.
; Use the quadratic formula to solve this.
; (quadratic 1.0 0.0 0.0) --> (0.0)
; (quadratic 1.0 3.0 -4.0) --> (-4.0 1.0)
(define (quadratic a b c)
(if
(REAL? (sqrt(- (* b b) (* (* 4 a) c))))
((let ((X (/ (+ (* b -1) (sqrt(- (* b b) (* (* 4 a) c)))) (* 2 a)))
(Y (/ (- (* b -1) (sqrt(- (* b b) (* (* 4 a) c)))) (* 2 a))))
(cond
((< X Y) (CONS X (CONS Y '())))
((> X Y) (CONS Y (CONS X '())))
((= X Y) (CONS X '()))
)))#f)
Error:
assertion-violation: attempt to call a non-procedure [tail-call]
('(0.0) '())
1>
assertion-violation: attempt to call a non-procedure [tail-call]
('(-4.0 1.0) '())
I'm not sure what it is trying to call. (0.0) and (-4.0 1.0) is my expected output so I don't know what it is trying to do.
Method #2:
;Returns the list of atoms that appear anywhere in the list,
;including sublists
; (flatten '(1 2 3) --> (1 2 3)
; (flatten '(a (b c) ((d e) f))) --> (a b c d e f)
(define (flatten lst)
(cond
((NULL? lst) '())
((LIST? lst) (APPEND (CAR lst) (flatten(CDR lst))))
(ELSE (APPEND lst (flatten(CDR lst))))
)
)
Error: assertion-violation: argument of wrong type [car]
(car 3)
3>
assertion-violation: argument of wrong type [car]
(car 'a)
I'm not sure why this is happening, when I'm checking if it is a list before I append anything.
Method #3
; Returns the value that results from:
; item1 OP item2 OP .... itemN, evaluated from left to right:
; ((item1 OP item2) OP item3) OP ...
; You may assume the list is a flat list that has at least one element
; OP - the operation to be performed
; (accumulate '(1 2 3 4) (lambda (x y) (+ x y))) --> 10
; (accumulate '(1 2 3 4) (lambda (x y) (* x y))) --> 24
; (accumulate '(1) (lambda (x y) (+ x y))) --> 1
(define (accumulate lst OP)
(define f (eval OP (interaction-environment)))
(cond
((NULL? lst) '())
((NULL? (CDR lst)) (CAR lst))
(ELSE (accumulate(CONS (f (CAR lst) (CADR lst)) (CDDR lst)) OP))
)
)
Error:
syntax-violation: invalid expression [expand]
#{procedure 8664}
5>
syntax-violation: invalid expression [expand]
#{procedure 8668}
6>
syntax-violation: invalid expression [expand]
#{procedure 8672}
7>
syntax-violation: invalid expression [expand]
#{procedure 1325 (expt in scheme-level-1)}
This one I have no idea what this means, what is expand?
Any help would be greatly appreciated
code has (let () ...) which clearly evaluates to list? so the extra parentheses seems odd. ((let () +) 1 2) ; ==> 3 works because the let evaluates to a procedure, but if you try ((cons 1 '()) 1 2) you should get an error saying something like application: (1) is not a procedure since (1) isn't a procedure. Also know that case insensitivity is deprecated so CONS and REAL? are not future proof.
append concatenates lists. They have to be lists. In the else you know since lst is not list? that lst cannot be an argument of append. cons might be what you are looking for. Since lists are abstraction magic in Scheme I urge you to get comfortable with pairs. When I read (1 2 3) I see (1 . (2 . (3 . ()))) or perhaps (cons 1 (cons 2 (cons 3 '()))) and you should too.
eval is totally inappropriate in this code. If you pass (lambda (x y) (+ x y)) which evaluates to a procedure to OP you can do (OP 1 2). Use OP directly.
I have got these functions
(define force!
(lambda (thunk)
(thunk)))
(define stream-head
(lambda (s n)
(if (zero? n)
'()
(cons (car s)
(stream-head (force! (cdr s))
(1- n))))))
(define make-stream
(lambda (seed next)
(letrec ([produce (lambda (current)
(cons current
(lambda ()
(produce (next current)))))])
(produce seed))))
(define make-traced-stream
(lambda (seed next)
(letrec ([produce (trace-lambda produce (current)
(cons current
(lambda ()
(produce (next current)))))])
(produce seed))))
(define stream-of-even-natural-numbers
(make-traced-stream 0
(lambda (n)
(+ n 2))))
(define stream-of-odd-natural-numbers
(make-traced-stream 1
(lambda (n)
(+ n 2))))
And I need to make a function that merges the last two, so that if I run
(stream-head (merge-streams stream-of-even-natural-numbers stream-of-odd-natural-numbers) 10)
I must get the output (0 1 2 3 4 5 6 7 8 9).. how is this done?
The best idea I had, which is wrong, have been:
(define merge-streams
(lambda (x y)
(cons (car x)
(merge-streams y (cdr x)))))
Here is a suggestion:
(define (merge-streams s1 s2)
(cond
[(empty-stream? s1) s2)] ; nothing to merge from s1
[(empty-stream? s2) s1)] ; nothing to merge from s2
[else (let ([h1 (stream-car s1)]
[h2 (stream-car s2)])
(cons h1
(lambda ()
(cons h2
(stream-merge (stream-rest s1)
(stream-rest s2))))))]))
It uses some helper functions that must be defined first.
(define depth-count
(lambda (l)
(let ((visited '())
(counter 0))
(let iter ((l l))
(cond ((pair? l)
(if (memq l visited)
(set! counter (+ 1 counter))
(begin
(set! visited (cons l visited))
(iter (car l))
(iter (cdr l)))))
(else '()))) counter)))
Imho, that else branch is unnecessary or just wrong, however that code seems to work, but I am not sure..
When I have .. let's say
(define l0 '(a b c))
(set-car! l0 l0)
(set-car! (cdr l0) l0)
(depth-count l0)
It should return 2, right? Is is correct then?
You are correct that the expression (else '()) is superfluous. It means that your cond expression will sometimes evaluate to the empty list. Hence, your inner let will sometimes evaluate to the empty list.
It is superfluous because you are not using the result of the inner let for anything. The result is discarded by the outer let, which returns the value of its final sub-expression: counter.
Yes, 2 is a reasonable (predictable) result for the input you've suggested.
As for its correctness, you really need to state more clearly what you are trying to achieve. The 'depth' of a 'cyclic list' is not a well-defined concept.
Here is my code:
(define (squares 1st)
(let loop([1st 1st] [acc 0])
(if (null? 1st)
acc
(loop (rest 1st) (* (first 1st) (first 1st) acc)))))
My test is:
(test (sum-squares '(1 2 3)) => 14 )
and it's failed.
The function input is a list of number [1 2 3] for example, and I need to square each number and sum them all together, output - number.
The test will return #t, if the correct answer was typed in.
This is rather similar to your previous question, but with a twist: here we add, instead of multiplying. And each element gets squared before adding it:
(define (sum-squares lst)
(if (empty? lst)
0
(+ (* (first lst) (first lst))
(sum-squares (rest lst)))))
As before, the procedure can also be written using tail recursion:
(define (sum-squares lst)
(let loop ([lst lst] [acc 0])
(if (empty? lst)
acc
(loop (rest lst) (+ (* (first lst) (first lst)) acc)))))
You must realize that both solutions share the same structure, what changes is:
We use + to combine the answers, instead of *
We square the current element (first lst) before adding it
The base case for adding a list is 0 (it was 1 for multiplication)
As a final comment, in a real application you shouldn't use explicit recursion, instead we would use higher-order procedures for composing our solution:
(define (square x)
(* x x))
(define (sum-squares lst)
(apply + (map square lst)))
Or even shorter, as a one-liner (but it's useful to have a square procedure around, so I prefer the previous solution):
(define (sum-squares lst)
(apply + (map (lambda (x) (* x x)) lst)))
Of course, any of the above solutions works as expected:
(sum-squares '())
=> 0
(sum-squares '(1 2 3))
=> 14
A more functional way would be to combine simple functions (sum and square) with high-order functions (map):
(define (square x) (* x x))
(define (sum lst) (foldl + 0 lst))
(define (sum-squares lst)
(sum (map square lst)))
I like Benesh's answer, just modifying it slightly so you don't have to traverse the list twice. (One fold vs a map and fold)
(define (square x) (* x x))
(define (square-y-and-addto-x x y) (+ x (square y)))
(define (sum-squares lst) (foldl square-y-and-addto-x 0 lst))
Or you can just define map-reduce
(define (map-reduce map-f reduce-f nil-value lst)
(if (null? lst)
nil-value
(map-reduce map-f reduce-f (reduce-f nil-value (map-f (car lst))))))
(define (sum-squares lst) (map-reduce square + 0 lst))
racket#> (define (f xs) (foldl (lambda (x b) (+ (* x x) b)) 0 xs))
racket#> (f '(1 2 3))
14
Without the use of loops or lamdas, cond can be used to solve this problem as follows ( printf is added just to make my exercises distinct. This is an exercise from SICP : exercise 1.3):
;; Takes three numbers and returns the sum of squares of two larger number
;; a,b,c -> int
;; returns -> int
(define (sum_sqr_two_large a b c)
(cond
((and (< a b) (< a c)) (sum-of-squares b c))
((and (< b c) (< b a)) (sum-of-squares a c))
((and (< c a) (< c b)) (sum-of-squares a b))
)
)
;; Sum of squares of numbers given
;; a,b -> int
;; returns -> int
(define (sum-of-squares a b)
(printf "ex. 1.3: ~a \n" (+ (square a)(square b)))
)
;; square of any integer
;; a -> int
;; returns -> int
(define (square a)
(* a a)
)
;; Sample invocation
(sum_sqr_two_large 1 2 6)
So, I've spent a lot of time reading and re-reading the ending of chapter 9 in The Little Schemer, where the applicative Y combinator is developed for the length function. I think my confusion boils down to a single statement that contrasts two versions of length (before the combinator is factored out):
A:
((lambda (mk-length)
(mk-length mk-length))
(lambda (mk-length)
(lambda (l)
(cond
((null? l) 0 )
(else (add1
((mk-length mk-length)
(cdr l))))))))
B:
((lambda (mk-length)
(mk-length mk-length))
(lambda (mk-length)
((lambda (length)
(lambda (l)
(cond
((null? l) 0)
(else (add1 (length (cdr l)))))))
(mk-length mk-length))))
Page 170 (4th ed.) states that A
returns a function when we applied it to an argument
while B
does not return a function
thereby producing an infinite regress of self-applications. I'm stumped by this. If B is plagued by this problem, I don't see how A avoids it.
Great question. For the benefit of those without a functioning DrRacket installation (myself included) I'll try to answer it.
First, let's use some sane (short) variable names, easily trackable by a human eye/mind:
((lambda (h) ; A.
(h h)) ; apply h to h
(lambda (g)
(lambda (lst)
(if (null? lst) 0
(add1
((g g) (cdr lst)))))))
The first lambda term is what's known as little omega, or U combinator. When applied to something, it causes that term's self-application. Thus the above is equivalent to
(let ((h (lambda (g)
(lambda (lst)
(if (null? lst) 0
(add1 ((g g) (cdr lst))))))))
(h h))
When h is applied to h, new binding is formed:
(let ((h (lambda (g)
(lambda (lst)
(if (null? lst) 0
(add1 ((g g) (cdr lst))))))))
(let ((g h))
(lambda (lst)
(if (null? lst) 0
(add1 ((g g) (cdr lst)))))))
Now there's nothing to apply anymore, so the inner lambda form is returned — along with the hidden linkages to the environment frames (i.e. those let bindings) up above it.
This pairing of a lambda expression with its defining environment is known as closure. To the outside world it is just another function of one parameter, lst. No more reduction steps left to perform there at the moment.
Now, when that closure — our list-length function — will be called, execution will eventually get to the point of (g g) self-application, and the same reduction steps as outlined above will again be performed (recalculating the same closure). But not earlier.
Now, the authors of that book want to arrive at the Y combinator, so they apply some code transformations to the first expression, to somehow arrange for that self-application (g g) to be performed automatically — so we may write the recursive function application in the normal manner, (f x), instead of having to write it as ((g g) x) for all recursive calls:
((lambda (h) ; B.
(h h)) ; apply h to h
(lambda (g)
((lambda (f) ; 'f' to become bound to '(g g)',
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst)))))) ; here: (f x) instead of ((g g) x)!
(g g)))) ; (this is not quite right)
Now after few reduction steps we arrive at
(let ((h (lambda (g)
((lambda (f)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))
(g g)))))
(let ((g h))
((lambda (f)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))
(g g))))
which is equivalent to
(let ((h (lambda (g)
((lambda (f)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))
(g g)))))
(let ((g h))
(let ((f (g g))) ; problem! (under applicative-order evaluation)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))))
And here comes trouble: the self-application of (g g) is performed too early, before that inner lambda can be even returned, as a closure, to the run-time system. We only want it to be reduced when the execution gets to that point inside the lambda expression, after the closure was called. To have it reduced before the closure is even created is ridiculous. A subtle error. :)
Of course, since g is bound to h, (g g) is reduced to (h h) and we're back again where we started, applying h to h. Looping.
Of course the authors are aware of this. They want us to understand it too.
So the culprit is simple — it is the applicative order of evaluation: evaluating the argument before the binding is formed of the function's formal parameter and its argument's value.
That code transformation wasn't quite right, then. It would've worked under normal order where arguments aren't evaluated in advance.
This is remedied easily enough by "eta-expansion", which delays the application until the actual call point: (lambda (x) ((g g) x)) actually says: "will call ((g g) x) when called upon with an argument of x".
And this is actually what that code transformation should have been in the first place:
((lambda (h) ; C.
(h h)) ; apply h to h
(lambda (g)
((lambda (f) ; 'f' to become bound to '(lambda (x) ((g g) x))',
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst)))))) ; here: (f x) instead of ((g g) x)
(lambda (x) ((g g) x)))))
Now that next reduction step can be performed:
(let ((h (lambda (g)
((lambda (f)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))
(lambda (x) ((g g) x))))))
(let ((g h))
(let ((f (lambda (x) ((g g) x)))) ; here it's OK
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst))))))))
and the closure (lambda (lst) ...) is formed and returned without a problem, and when (f (cdr lst)) is called (inside the closure) it is reduced to ((g g) (cdr lst)) just as we wanted it to be.
Lastly, we notice that (lambda (f) (lambda (lst ...)) expression in C. doesn't depend on any of the h and g. So we can take it out, make it an argument, and be left with ... the Y combinator:
( ( (lambda (rec) ; D.
( (lambda (h) (h h))
(lambda (g)
(rec (lambda (x) ((g g) x)))))) ; applicative-order Y combinator
(lambda (f)
(lambda (lst)
(if (null? lst) 0
(add1 (f (cdr lst)))))) )
(list 1 2 3) ) ; ==> 3
So now, calling Y on a function is equivalent to making a recursive definition out of it:
( y (lambda (f) (lambda (x) .... (f x) .... )) )
=== define f = (lambda (x) .... (f x) .... )
... but using letrec (or named let) is better — more efficient, defining the closure in self-referential environment frame. The whole Y thing is a theoretical exercise for the systems where that is not possible — i.e. where it is not possible to name things, to create bindings with names "pointing" to things, referring to things.
Incidentally, the ability to point to things is what distinguishes the higher primates from the rest of the animal kingdom ⁄ living creatures, or so I hear. :)
To see what happens, use the stepper in DrRacket.
The stepper allows you to see all intermediary steps (and to go back and forth).
Paste the following into DrRacket:
(((lambda (mk-length)
(mk-length mk-length))
(lambda (mk-length)
(lambda (l)
(cond
((null? l) 0 )
(else (add1
((mk-length mk-length)
(cdr l))))))))
'(a b c))
Then choose the teaching language "Intermediate Student with lambda".
Then click the stepper button (the green triangle followed by a bar).
This is what the first step looks like:
Then make an example for the second function and see what goes wrong.