I am tasked with solving a maze using the method of backtracking and recursion. This is more of a conceptual question about this concept.
How is the backtracking call ever reached? From all the examples I have seen it looks as though recursion is always called immediately before the backtracking step, so that backtracking can not be reached. Can anyone explain to me how the backtracking step is reached?
Backtracking happens when the recursion returns. For example, if you are at location A, and there are two neighboring locations, B and C. You could make a recursive call on B. When it has finished exploring that part of the maze, it will return (ie, backtrack) to the call at location A, which will then make a new recursive call on location C.
Related
Is it theoretically possible to transform every kind of general-recursion into tail-recursion? Are they equivalent for example from a lambda-calculus point of view? That's a debate between me and an acquaintance.
My view is that it's not possible everytime. For example if you have a function which calls itself recursively twice or three times, then you can't make all the recursive calls into tail-calls, right? Or is there always a way to reduce the number of recursive calls to one single recursive call?
No. If you cannot rewrite your algorithm to have only tail calls, like in tree traversal, at least one call will not be in tail position.
Some may say loop + explicit stack is iterative, but IMO it's still recursion and a tree traversal will grow the stack just as general recursion.
I am learning data structure and algorithms. I found it especially difficult to understand recursions.
So I have the following questions. But they are not related to any specific code.
When I implement methods, when/where should I consider recursion?
In general coding convention, should I prefer recursion over simple iteration if they are both feasible?
How to actually comprehend most possible forms of recursion so I can think of them when I need? What is the best way to learn it? (Any related book or website?) Is there any pattern?
I know the question may sounds unconstructive if you find recursion simple and natural.
But for me it doesn't align with my intuition well. I do appreciate any help.
1
Very often recursive solutions to problems are smaller when data can be seen as similar. Eg. If you have a binary tree and you want to get the sum of all the leaf nodes you define sum-tree as If it's a leaf node, it's sum is it's value, if it's not a leaf node it the addition of the sum of both sub-trees.
Here's a Scheme implementation of my text
(define (sum-tree tree)
(if (leaf? tree)
(node-value tree)
(+ (sum-tree (node-left tree))
(sum-tree (node-right tree)))))
Or the same in Java, defined as a method in the Node class.
public int sum()
{
if ( isLeaf() )
return value;
else
return left.sum() + right.sum();
}
An iterative solution to this would be longer and harder to read. In this case you should prefer recursion.
2
It depends. If you are programming in Python or Java you should not since they donæt have tail recursion. With Scheme however, it's the only way to go. If your language supports tail recursion you should pick recursion when it makes clearer code.
3
Learn by doing. You need to write some algorithms that uses recursion as a tool. Use paper to follow the flow of the stack if you are unsure of the flow. Learning some Scheme or a similar functional language might help you a lot.
Recursion can be used when you are repeating the same thing over and over. For example, you are traversing a tree, you can use a recursion method to go to the left or right child.
I would go for the one that is easier to read. Generally, simple iteration will be faster as it does not have any overhead (recursion has some overhead, and can cause stack overflow if the levels are to deep, while simple iteration won't). But for some case, writing a recursive function is a lot easier than writing the equivalent in the simple iteration.
I would rather see the problem first and then decide whether I need recursion to solve it, not vice versa. Any algorithm book should be good enough. Perhaps you can start over reading http://en.wikipedia.org/wiki/Recursion to begin with. There is a simple example there about recursion, which I think you will be able to implement too using simple iteration.
At first, wrapping my head around recursion was hard as well. When I was learning recursion it was during school with Java. I found it more often I would use recursion over iterators as they were annoying to write in Java. However, I learned Ruby and I found myself writing recursive methods less and less. Then, I learned Elixir and Erlang and found myself writing a lot of recursive functions. My point? Some tools will give themselves for writing with certain style.
Now to answer your questions, since you're just starting to learn recursion, I would suggest diving deep into them and trying to get comfortable with them writing them as much as you can.
Certain tasks are much better off with recursion (e.g. Fibonacci sequence, traversing trees, etc..). Some other's you're better off writing a simple loop. However, note that you can write any recursive method with a loop. It might get tricky on certain occasions though.
All in all, recursion is actually a pretty cool concept once you get the hang of it.
Take a look at this question that relates to recursion: Erlang exercise, creating lists
I'd go for a study of some well known recursive algorithms. For instance, you could try to implement a factorial computation, or to get all the paths lengths in a tree.
By doing that you'll (hopefully) see how the recursive approach helps to simplify the code, and why it is a good approach in these particular cases. This could give you some ideas for future applications :)
I was reading the book, Structure and Interpretation of Computer Programs, where in it tells about the distinction between a recursive procedure and recursive process, and similarly between iterative procedure and iterative process. So, a recursive procedure could still generate an iterative process.
My question is: given a procedure which generates a recursive process, can you always write another procedure that achieves the same result but generates an iterative process?
The specific problem that I was trying to solve was to write a procedure which does an in-order traversal of a binary search tree but generates an iterative process. I know how you can use a stack to get an iterative procedure for this problem. However, that still generates a recursive process (correct me if I am wrong here).
Thanks,
Abhinav.
Some tasks are truly impossible to solve with linear iterative processes (e.g. tree recursion, which is impossible to convert to tail recursion). You either have to use the stack built into your platform, or re-create it yourself within the language (usually a much less efficient and uglier solution).
So if you define 'recursion' as 'using a stack to store different invocations of the same code', then yes, recursion sometimes is absolutely required.
If you define 'recursion' as 'a function in my language (eventually) calling itself', then you can get by without explicit recursion by re-implementing recursiveness yourself, as describes above. This is only useful if your language doesn't provide recursive procedures, or not enough stack space, or has similar limitations. (For instance, early Fortran's didn't have recursive procedures. Of course, they also didn't have the dynamic data structures that you would need to simulate them! Personally, I have never come across an actual example where implementing pseudo-recursion was the right solution.)
Read this former SO post:
Design patterns for converting recursive algorithms to iterative ones
there are a lot of good answers there which may help you further.
Any tail recursive process can be transformed into an iterative one.
But not all recursive processes can be transformed into an iterative one.
With respect to using recursion over non-recursive methods in sorting algorithms or, for that matter, any algorithm what are its pros and cons?
For the most part recursion is slower, and takes up more of the stack as well. The main advantage of recursion is that for problems like tree traversal it make the algorithm a little easier or more "elegant".
Check out some of the comparisons:
link
Recursion means a function calls repeatedly
It uses system stack to accomplish its task. As stack uses LIFO approach
and when a function is called the controlled is moved to where function is defined which has it is stored in memory with some address, this address is stored in stack
Secondly, it reduces a time complexity of a program.
Though bit off-topic,a bit related. Must read. : Recursion vs Iteration
All algorithms can be defined recursively. That makes it much, much easier to visualize and prove.
Some algorithms (e.g., the Ackermann Function) cannot (easily) be specified iteratively.
A recursive implementation will use more memory than a loop if tail call optimization can't be performed. While iteration may use less memory than a recursive function that can't be optimized, it has some limitations in its expressive power.
Any algorithm implemented using recursion can also be implemented using iteration.
Why not to use recursion
It is usually slower due to the overhead of maintaining the stack.
It usually uses more memory for the stack.
Why to use recursion
Recursion adds clarity and (sometimes) reduces the time needed to write and debug code (but doesn't necessarily reduce space requirements or speed of execution).
Reduces time complexity.
Performs better in solving problems based on tree structures.
For example, the Tower of Hanoi problem is more easily solved using recursion as opposed to iteration.
I personally prefer using Iterative over recursive function. Especially if you function has complex/heavy logic and number of iterations are large. This because with every recursive call call stack increases. It could potentially crash the stack if you operations are too large and also slow up process.
To start:
Pros:
It is the unique way of implementing a variable number of nested loops (and the only elegant way of implementing a big constant number of nested loops).
Cons:
Recursive methods will often throw a StackOverflowException when processing big sets. Recursive loops don't have this problem though.
To start :
Recursion:
A function that calls itself is called as recursive function and this technique is called as recursion.
Pros:
1. Reduce unnecessary calling of functions.
2. Through Recursion one can solve problems in easy way while its iterative solution is very big and complex.
3. Extremely useful when applying the same solution.
Cons:
1. Recursive solution is always logical and it is very difficult to trace.
2. In recursive we must have an if statement somewhere to force the function to return without the recursive call being executed, otherwise the function will never return.
3. Recursion uses more processor time.
Expressiveness
Most problems are naturally expressed by recursion such as Fibonacci, Merge sorting and quick sorting. In this respect, the code is written for humans, not machines.
Immutability
Iterative solutions often rely on varying temporary variables which makes the code hard to read. This can be avoided with recursion.
Performance
Recursion is not stack friendly. Stack can overflow when the recursion is not well designed or tail optimization is not supported.
Some situation would arise where you would have to abandon recursion in a problem where recursion appears to be to your advantage, this is because for problems where your recursion would have to occur thousand of times this would result in a stackoverflow error even though your code did not get stuck in an infinite recursion. Most programming languages limits you to a number of stack calls, so if your recursion goes beyond this limit, then you might consider not using recursion.
We should use recursion in following scenarios:
when we don't know the finite number of iteration for example our fuction exit condition is based on dynamic programming (memoization)
when we need to perform operations on reverse order of the elements. Meaning we want to process last element first and then n-1, n-2 and so on till first element
Recursion will save multiple traversals. And it will be useful, if we can divide the stack allocation like:
int N = 10;
int output = process(N) + process(N/2);
public void process(int n) {
if (n==N/2 + 1 || n==1) {
return 1;
}
return process(n-1) + process(n-2);
}
In this case only half stacks will be allocated at any given time.
Recursion gets a bad rep, I'm always surprised by the number of developers that wont even touch recursion because someone told them it was evil incarnate.
I've learned through trial and error that when done properly recursion can be one of the fastest ways to iterate over something, it is not a steadfast rule and each language/ compiler/ engine has it's own quirks so mileage will vary.
In javascript I can reliably speed up almost any iterative process by introducing recursion with the added benefit of reducing side effects and making the code more clear concise and reusable. Also pro tip its possible to get around the stack overflow issue (and no you dont disable the warning).
My personal Pros & Cons:
Pros:
- Reduces side effects.
- Makes code more concise and easier to reason about.
- Reduces system resource usage and performs better than the traditional for loop.
Cons:
- Can lead to stack overflow.
- More complicated to setup than a traditional for loop.
Mileage will vary depending on language/ complier/ engine.
I have been learning scheme and I like to know the difference between the two. Thanks.
Accumulative recursion uses an extra parameter in which we collect new information as we go deeper into the recursion. The computed value is returned unchanged back up through the layers of recursion.
Structural recursion performs much of the work on the way back up through the layers of recursion.Accumulative recursion is often more efficient than stack recursion.