What are the best practices for preventing stack overflow when using recursion?

To prevent stack overflow in recursion: 1. Use a base case to stop recursion. 2. Optimize with tail recursion. 3. Cache results with memoization. 4. Limit recursion depth. 5. Test thoroughly. 6. Consider iterative solutions. 7. Use proper data structures. 8. Leverage Tail Call Optimization (TCO) where available.

I was helped by thinking about base cases as the “finish line” of a recursive function. What is the ultimate point you are trying to reach before you have everything you need. Recursive call = Keep going Base case return = The finish line

"USE OF GLOBAL VARIABLE", Adding breakers on top of execution,Use of optimisation techniques such as tail recursion or iterations

Set a Base Case: Always define a clear base case for your recursive function to stop calling itself. Without a base case, or if the base case is never reached due to incorrect logic, the recursion will continue indefinitely, leading to a stack overflow.

I do not like the term "best practices" because usually it actually means "most agreed practices". That said, in order to prevent stack overflow when using recursion one should look into the following: 1. Is your data set limited in size? If the data set is not supposed to ever grow beyond a certain point and your automated tests tell you that you can scale well ( concurrency accounted for) then recursion is fine. 2. Does your compiler/interpreter provide stack optimization features? The stack could be handled in such a way that a reduced and controlled amount of data is always kept in it. Most popular languages as of 2023 lack such a feature. 3. Is it a no? Then your remaining options are iteration or recursive partitioning/decomposition.

Avoid using a global variable. If the recursive function can be called from multiple places concurrently, a global variable won't work. Edited in response to another contribution: Yes, reentrancy is a separate problem that isn't directly related to recursion, but I still think it's worth suggesting to avoid global variables (unless you're working in a limited environment that can't handle the added parameter).

A global variable can only be a problem if it messes up the limiting condition; otherwise the fact that it's global is irrelevant. What you're discussing is re-entrancy, which is a separate problem not connected with recursion.

Choosing the appropriate limit of depth can be challenging. Setting it too high might still risk a stack overflow, while setting it too low may truncate the recursion prematurely, affecting the quality of the result.

Limit the Depth of Recursion: Manually setting a limit to the depth of recursion can prevent stack overflows. This involves tracking the depth of recursion and returning or throwing an error once a maximum depth is reached.

The article says it, but the point is worth emphasizing: While you can structure your recursive function to take advantage of tail recursion; it is an optimization technique done by the compiler that is outside of the developer's control. On the other hand, structuring your code this way can still help somewhat because most compilers will optimize to not preserve stack for variables that are beyond there final use when the recursive call is made.

The best way to avoid having problems with recursion is essentially not using recursion. Most of the times you can just loop through your hierarchy and get it done. It will be more efficient as you don't need to build contexts on each method call, you will be able to parallelize if your problem allows to it, and you will avoid problems like stack overflows. In case you cannot serialize your problem and therefore make it iterable, you need to be 100 % sure your base condition is good enough, and maybe keep track of visited items, so you can (maybe) avoid going through all the items reaching the limit.

Max -- nope. What has been proven is that any _tail-recursive_ algorithm can also be solved iteratively. If it isn't tail-recursive, there may well be NO iterative equivalent. Later -- thanks for the addition of the article link. Very interesting! As I mentioned below, I do a lot of computer language manipulation, and the recursive nature of almost all such grammars dictates a recursive approach for clarity if nothing else. (Interestingly, Backus Naur Form or BNF, which I execute at parse time, is itself recursively defined!)

IF POSSIBLE. "Sometimes" is the key word. (although I would prefer to use "Most of the time"). In my experience the only time this can't be done is in somewhat contrived problems. I hear scientific computing sometimes runs into this though.

Use Non-Recursive Data Structures: For example, instead of using recursive function calls, you can manage the call stack manually using a stack data structure, which can sometimes be more efficient and less risky.

Sometimes nothings works and the only solution is to add a time-based circuit breaker on top of execution. this limits the overall abuse of recursion and we can mix it with telemetry logging data to prevent over abuse of recursion

I deal with parsing and automated manipulation of computer languages a lot (analysis, transformation, even translation, see WWW.XTRAN-LLC.com), and most are recursively defined (e.g., an expression can have an expression as its term). In this case, the recursion is naturally self-limiting (e.g., you reach the deepest term in the outer expression; since its terms are not expressions, recursion ends). Since computer languages are mostly inherently recursive in nature, we must use recursion to deal with them -- both to parse them and to manipulate them. Recursion is not inherently good or bad; it's just a (very cool!) tool for solving problems.

I don’t see anything about dynamic programming in here? Dynamic programming is beneficial because it stores the results of subproblems, eliminating the need to recompute them, which drastically reduces the number of computations. Memoization improves efficiency, particularly in problems with overlapping subproblems, leading to faster and more resource-efficient algorithms.

If Recursion solution cannot be converted to Iterative solution using simple loops and depth is causing to exceed memory available, use Stack data structure, so that memory is allocated in heap - the dynamically allocated memory instead of process thread stack.