Recursive & Iterative Binary Search Tree Implementations within Rust
This crate contains Recursive & Iterative Binary Search Tree Implementations. All common operations are included along with common traversal iterators.
All elements within the Binary Search Trees must implement the Ord trait.
It is also important to note that RecursiveBST is more likely to blow the stack.
For more information on why that is the case, please have a look at
The Story of Tail Call Optimizations in Rust.
I have made this library with the personal goals of learning and solidifying concepts such as ownership
, borrowing
, generics
and lifetimes
. I cannot promise that the implementations are particularly efficient, or if they are, it
was not at the forefront of my mind.
That being said, there are some areas I would love to improve upon which include:
- Write idiomatic code.
- Effectively use macro_rules! to reduce large portions of repetitive code.
- Implement a pretty_print() function to display the binary search trees nicely.
- Implementing the Drop trait for iterative node cleanup.
- Pre-allocating space on the heap for nodes to reduce inefficiency of inserts.
I'm more than happy to accept (and encourage) contributions if anyone is kind enough to do so. (Please look at CONTRIBUTING!)
use bst_rs::{BinarySearchTree, IterativeBST, RecursiveBST};
// Create new empty binary search trees
let mut iterative_bst = IterativeBST::new();
assert!(iterative_bst.is_empty());
let mut recursive_bst = RecursiveBST::new();
assert!(recursive_bst.is_empty());
// Insert elements (no duplicates are allowed)
iterative_bst.insert(10);
iterative_bst.insert(10); // Element is not inserted
iterative_bst.insert(5);
iterative_bst.insert(2);
iterative_bst.insert(15);
iterative_bst.insert(25);
assert_eq!(iterative_bst.size(), 5);
recursive_bst.insert(10);
recursive_bst.insert(10); // Element is not inserted
recursive_bst.insert(5);
recursive_bst.insert(2);
recursive_bst.insert(15);
recursive_bst.insert(25);
assert_eq!(recursive_bst.size(), 5);
// Check if element exists
assert!(iterative_bst.contains(&5)); // true
assert!(!iterative_bst.contains(&0)); // false
assert!(recursive_bst.contains(&5)); // true
assert!(!recursive_bst.contains(&0)); // false
// Remove elements
iterative_bst.remove(&10);
iterative_bst.remove(&50); // No change to tree as element does not exist
assert_eq!(iterative_bst.size(), 4);
recursive_bst.remove(&10);
recursive_bst.remove(&50); // No change to tree as element does not exist
assert_eq!(recursive_bst.size(), 4);
// Get height of tree
assert_eq!(iterative_bst.height(), Some(2));
assert_eq!(recursive_bst.height(), Some(2));
// Get minimum element of tree
assert_eq!(iterative_bst.min(), Some(&2));
assert_eq!(recursive_bst.min(), Some(&2));
// Get maximum element of tree
assert_eq!(iterative_bst.max(), Some(&25));
assert_eq!(recursive_bst.max(), Some(&25));
// Retrieve reference to element in tree
assert_eq!(iterative_bst.retrieve(&5), Some(&5));
assert_eq!(iterative_bst.retrieve(&100), None); // Element does not exist so None is returned
assert_eq!(recursive_bst.retrieve(&5), Some(&5));
assert_eq!(recursive_bst.retrieve(&100), None); // Element does not exist so None is returned
// View pre-order, in-order, post-order and level-order traversals
assert_eq!(iterative_bst.pre_order_vec(), vec![&15, &5, &2, &25]);
assert_eq!(iterative_bst.in_order_vec(), vec![&2, &5, &15, &25]);
assert_eq!(iterative_bst.post_order_vec(), vec![&2, &5, &25, &15]);
assert_eq!(iterative_bst.level_order_vec(), vec![&15, &5, &25, &2]);
assert_eq!(recursive_bst.pre_order_vec(), vec![&15, &5, &2, &25]);
assert_eq!(recursive_bst.in_order_vec(), vec![&2, &5, &15, &25]);
assert_eq!(recursive_bst.post_order_vec(), vec![&2, &5, &25, &15]);
assert_eq!(recursive_bst.level_order_vec(), vec![&15, &5, &25, &2]);
// Compare equality/in-equality of trees
assert_eq!(iterative_bst.asc_order_vec(), recursive_bst.asc_order_vec());
assert_ne!(iterative_bst, IterativeBST::new());
assert_ne!(recursive_bst, RecursiveBST::new());
Please read the CONTRIBUTING.md before contributing! (Thank you!)
The book Learn Rust With Entirely Too Many Linked Lists inspired me to try and implement Binary Search Trees within the language. I had also been wanting to create my first library for other crates to use.