reverse linked list - Recursion - recursion

Sorry if this is a very basic question, I am just trying to learn recursion.
The below code can reverse a linked list.
I understand the logic until line 3, but I am confused when line 4 will be called (n.next=prev) since the function gets called again before executing this line.
Can someone let me know the flow of this recursion?
void reverse(node n, node prev) {
if (n == null) { newroot = prev; return; }
reverse(n.next, n);
n.next = prev;
}

As soon as n hits null and reverse function return it will backtrack from there to it's calling function all the way to it's first calling function.
UPDATE: See the comments below for a more complete explanation.

Related

What happens after non-tail recursion bottoms out

I am new to recursion, and have been looking at non-tail recursion. I believe this is where the recursive call is not at the end of the function. I was looking at some recursive code examples, and I am confused about when and how the code after the recursive call is executed. To be more specific, when the current line of the program reaches the recursive call, is that last bit of code executed before actually executing the entire function again, or does the current line of execution immediately jump back to the beginning of the function, only to execute that remaining bit of code after the entire recursion bottoms out? Can anybody please clarify how this works for me?
Imagine this code here: (I'm using JS here, but it applies to all eager languages)
function add(a, b) {
return a + b;
}
function sub(a, b) {
return a - b;
}
function fib(n) {
if (n < 2) {
return n;
} else {
return add(
fib(sub(n, 2)),
fib(sub(n, 1)),
);
}
}
console.log(fib(10));
Now when n is 2 or more we we add the result of calling fib on the two predecessors to n. The order between some of the calls are JS engines choice, but sub needs to be called and return before fib can get a value and add needs to be called when both it's arguments have results. This can be rewritten as tail calls using continuation passing style:
function cadd(a, b, k) {
k(a + b);
}
function csub(a, b, k) {
k(a - b);
}
function cfib(n, k) {
if (n < 2) {
k(n);
} else {
csub(n, 2, n2 =>
cfib(n2, rn2 =>
csub(n, 1, n1 =>
cfib(n1, rn1 =>
cadd(rn2, rn1, k)))));
}
}
cfib(10, console.log);
Here you see the order which was engines choice is explicit left to right. Each call does one thing then the continuation is called with that result. Notice also that this never returns anything. "return" is only done by continuation, yet it does the exact same thing as the previous code.
In many languages they would compile to the same.

tail rec kotlin list

I'm trying to do some operations that would cause a StackOverflow in Kotlin just now.
Knowing that, I remembered that Kotlin has support for tailrec functions, so I tried to do:
private tailrec fun Turn.debuffPhase(): List<Turn> {
val turns = listOf(this)
if (facts.debuff == 0 || knight.damage == 0) {
return turns
}
// Recursively find all possible thresholds of debuffing
return turns + debuff(debuffsForNextThreshold()).debuffPhase()
}
Upon my surprise that IDEA didn't recognize it as a tailrec, I tried to unmake it a extension function and make it a normal function:
private tailrec fun debuffPhase(turn: Turn): List<Turn> {
val turns = listOf(turn)
if (turn.facts.debuff == 0 || turn.knight.damage == 0) {
return turns
}
// Recursively find all possible thresholds of debuffing
val newTurn = turn.debuff(turn.debuffsForNextThreshold())
return turns + debuffPhase(newTurn)
}
Even so it isn't accepted. The important isn't that the last function call is to the same function? I know that the + is a sign to the List plus function, but should it make a difference? All the examples I see on the internet for tail call for another languages allow those kind of actions.
I tried to do that with Int too, that seemed to be something more commonly used than addition to lists, but had the same result:
private tailrec fun discoverBuffsNeeded(dragon: RPGChar): Int {
val buffedDragon = dragon.buff(buff)
if (dragon.turnsToKill(initKnight) < 1 + buffedDragon.turnsToKill(initKnight)) {
return 0
}
return 1 + discoverBuffsNeeded(buffedDragon)
}
Shouldn't all those implementations allow for tail call? I thought of some other ways to solve that(Like passing the list as a MutableList on the parameters too), but when possible I try to avoid sending collections to be changed inside the function and this seems a case that this should be possible.
PS: About the question program, I'm implementing a solution to this problem.
None of your examples are tail-recursive.
A tail call is the last call in a subroutine. A recursive call is a call of a subroutine to itself. A tail-recursive call is a tail call of a subroutine to itself.
In all of your examples, the tail call is to +, not to the subroutine. So, all of those are recursive (because they call themselves), and all of those have tail calls (because every subroutine always has a "last call"), but none of them is tail-recursive (because the recursive call isn't the last call).
Infix notation can sometimes obscure what the tail call is, it is easier to see when you write every operation in prefix form or as a method call:
return plus(turns, debuff(debuffsForNextThreshold()).debuffPhase())
// or
return turns.plus(debuff(debuffsForNextThreshold()).debuffPhase())
Now it becomes much easier to see that the call to debuffPhase is not in tail position, but rather it is the call to plus (i.e. +) which is in tail position. If Kotlin had general tail calls, then that call to plus would indeed be eliminated, but AFAIK, Kotlin only has tail-recursion (like Scala), so it won't.
Without giving away an answer to your puzzle, here's a non-tail-recursive function.
fun fac(n: Int): Int =
if (n <= 1) 1 else n * fac(n - 1)
It is not tail recursive because the recursive call is not in a tail position, as noted by Jörg's answer.
It can be transformed into a tail-recursive function using CPS,
tailrec fun fac2(n: Int, k: Int = 1): Int =
if (n <= 1) k else fac2(n - 1, n * k)
although a better interface would likely hide the continuation in a private helper function.
fun fac3(n: Int): Int {
tailrec fun fac_continue(n: Int, k: Int): Int =
if (n <= 1) k else fac_continue(n - 1, n * k)
return fac_continue(n, 1)
}

Why does Infinite loop occurs while reversing the linked list using recursion

I am a beginner in data structures. Lets assume that I have a linked list of 5 elements. I was writing the below code to reverse the linked list using recursion:
void reverse (node* p)
{
if (p->next == NULL)
{
head = p;
return;
}
reverse (p->next);
node* q = p->next;
q->next = p;
p->next = NULL;
}
In the above code, head node is passed initially as an argument. This code runs well;but the question is why are we using the line?
p->next = NULL;
If I did not add that line, it becomes an infinite loop. But even if that line is not added, p->next is assigned with the previous node's address in the following stack unwinding. So why does it cause an infinite loop if that line is not added?

How does recursion work its way back?

I'm working to understand recursion more in depth and I'm struggling with WHY it works the way it does. I know that this function returns the square of the previous return (2, 4, 16, 256, etc.), but I'm wonder how it gets the answer.
My understanding of recursion is that it iterates back down to the base case, but that leads me to believe that it would eventually always return the base case. How does it work its way back up to returning something new every time?
int p1a(int num) {
if (num == 1) { return 2; }
else {
return pow(p1a(num-1), 2);
}
}
Here's an example of my thinking
num = 3
passes through the base case and hits pow(p1a(num-1), 2)
moves back to the start
again passes through the base case and hits pow(p1a(num-1), 2)
at this point, num = 1, so it would return 2
How is it working its way back up to return 16? I understand what the function returns, but I'm stuck on the process of getting there.
You're thinking about the steps linearly, while the execution is actually nested (represented by indenting):
call p1a(3)
call p1a(2)
call p1a(1)
return 2
return pow(2, 2)
return pow(4, 2)
So the final return returns the value 16.

Backtracking recursively with multiple solutions

function BACKTRACKING-SEARCH(csp) returns a solution, or failure
return RECURSIVE- BACKTRACKING({ }, csp)
function RECURSIVE-BACKTRACKING(assignment,csp) returns a solution, or failure
if assignment is complete then
return assignment
var ←SELECT-UNASSIGNED-VARIABLE(VARIABLES[csp],assignment,csp)
for each value in ORDER-DOMAIN-VALUES(var,assignment,csp) do
if value is consistent with assignment according to CONSTRAINTS[csp] then
add {var = value} to assignment
result ← RECURSIVE-BACKTRACKING(assignment, csp)
if result ̸= failure then
return result
remove {var = value} from assignment
return failure
This is a backtracking recursion algorythm pseudocode from AIMA. However, I don't understand if it returns ALL possible solutions or just first one found. In case it is the last option, could you please help me modify it to return a list of possible solutions instead (or at least updating some global list).
EDIT: I implemented this algorithm in Java. However, there is one problem:
if I don't return assignment, but save it in result instead, the recursion stop condition fails (i.e. it doesn't exist anymore). How can I implement another stop-condition? Maybe I should return true in the end?
Here is my code :
/**
* The actual backtracking. Unfortunately, I don't have time to implement LCV or MCV,
* therefore it will be just ordinary variable-by-variable search.
* #param line
* #param onePossibleSituation
* #param result
*/
public static boolean recursiveBacktrack(Line line, ArrayList<Integer> onePossibleSituation, ArrayList<ArrayList<Integer>> result){
if (onePossibleSituation.size() == line.getNumOfVars()){
// instead of return(assignment)
ArrayList<Integer> situationCopy = new ArrayList<Integer>();
situationCopy.addAll(onePossibleSituation);
result.add(situationCopy);
onePossibleSituation.clear();
}
Block variableToAssign = null;
// iterate through all variables and choose one unassigned
for(int i = 0; i < line.getNumOfVars(); i++){
if(!line.getCspMiniTaskVariables().get(i).isAssigned()){
variableToAssign = line.getCspMiniTaskVariables().get(i);
break;
}
}
// for each domain value for given block
for (int i = line.getCspMiniTaskDomains().get(variableToAssign.getID())[0];
i <= line.getCspMiniTaskDomains().get(variableToAssign.getID())[0]; i++){
if(!areThereConflicts(line, onePossibleSituation)){
//complete the assignment
variableToAssign.setStartPositionTemporary(i);
variableToAssign.setAssigned(true);
onePossibleSituation.add(i);
//do backtracking
boolean isPossibleToPlaceIt = recursiveBacktrack(line,onePossibleSituation,result);
if(!isPossibleToPlaceIt){
return(false);
}
}
// unassign
variableToAssign.setStartPositionTemporary(-1);
variableToAssign.setAssigned(false);
onePossibleSituation.remove(i);
}
// end of backtracking
return(false);
}
This code checks if solution found and if it is, returns the solution. Otherwise, continue backtracking. That means, it returns the first solution found.
if result ̸= failure then
return result
remove {var = value} from assignment
You can modify it like that:
if result ̸= failure then
PRINT result // do not return, just save the result
remove {var = value} from assignment
Or, better, modify this part:
if assignment is complete then
print assignment
return assignment // print it and return
About edited question:
First, return true in the first if, so recursion will know that it found a solution. The second step, there is a mistake, probably:
if(!isPossibleToPlaceIt){
return(false);
}
Should be
if(isPossibleToPlaceIt){
return(true);
}
Because if your backtracking has found something, it returns true, which means you don't have to check anything else any longer.
EDIT#2: If you want to continue backtracking to find ALL solutions, just remove the whole previous if section with return:
//if(isPossibleToPlaceIt){
// return(true);
//}
So we will continue the search in any way.

Resources