backtracking_concepts

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Why is recursion an effective way to implement a backtracking algorithm?
Backtracking uses recursion to produce output instead of the print() function. Backtracking needs to explore multiple options, which is hard to do with loops and collections. Backtracking cannot be implemented without recursion. Recursion works well because the memory of decisions and points to go back to are represented by the recursive call stack. Recursion works well because it uses less memory than looping. (order shuffled)
What is a decision tree, and how are decision trees important for backtracking?
A decision tree is a description of the set of choices that can be made by a recursive backtracking function at any point in the algorithm. A decision tree is a collection that stores binary data. A decision tree is the org chart at a company that they use to help make programming project decisions. A decision tree is a structure inside the Python interpreter that helps it run recursive code. A decision tree is the concept of a function calling itself. (order shuffled)

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