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Zip tree

Zip tree is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Zip tree rather than just read about it. In short: The zip tree was introduced as a variant of random binary search tree by Robert Tarjan, Caleb Levy, and Stephen Timmel. Zip trees are similar to max treaps except ranks are generated through a geometric distribution and maintain their max-heap property during insertions and deletions through unzipping and zipping rather than tree rotations.

Zip tree — main illustration
Zip tree — illustration

Key takeaways

  • Zip tree belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Zip tree to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Zip tree from memory before moving on to harder problems.

Reference excerpt

The zip tree was introduced as a variant of random binary search tree by Robert Tarjan, Caleb Levy, and Stephen Timmel. Zip trees are similar to max treaps except ranks are generated through a geometric distribution and maintain their max-heap property during insertions and deletions through unzipping and zipping rather than tree rotations. Nodes of the tree contain a distinct, comparable key and a numeric rank. The tree is max heap ordered with respect to the ranks with ties broken in favor of smaller keys. Nodes of the tree must contain distinct keys but allow for duplicate ranks. The rank tie-breaker favoring smaller keys creates a bias in the tree favoring smaller nodes. A slightly modified zip tree variant, zip-zip trees address this bias by introducing a different tie-breaker with a second rank.

Operations Zip trees support the operations of a binary search tree. The main implementation differences come through the zip tree's implementation of insert and delete through unzipping and zipping paths to maintain the heap ordering of the tree. The time it takes to insert or delete a node u is equal to the time to search for u plus the time for unzipping or zipping. The time it takes to unzip or zip is proportional to one plus the number of nodes on the path(s) being unzipped/zipped. The expected depth of any node in a zip tree is at most 1.5 log n, making the expected running time of the insert, delete, and search operations all O(log n).

Insertion When inserting a node x into a zip tree, first generate a new rank from a geometric distribution with a probability of success of 1/2. Let x.key be the key of the node x, and let x.rank be the rank of the node x.

Then, follow the search path for x in the tree until finding a node u such that u.rank <= x.rank and u.key < x.key. Continue along the search path for x, "unzipping" every node v passed by placing them either in path P if v.key < x.key, or path Q if v.key > x.key. Keys must be unique so if at any point v.key = x.key, the search stops and no new node is inserted. Once the search for x is complete, x is inserted in place of the node u. The top node of the path P becomes the left child of x and the top node of Q becomes the right child. The parent and child pointers between u and u.parent will be updated accordingly with x, and if u was previously the root node, x becomes the new root.

Deletion When deleting a node x, first search the tree to find it. If no node is found with the same key as x.key, no deletion occurs. Once x is found, continue two searches down the left and right subtrees of x, "zipping" together the right spine of the left subtree and left spine of the right subtree into one path R in decreasing order by rank. While creating this path top-down, nodes are added as left and right children of their parent accordingly based on their keys. Once the path R is complete, the root of the path will replace x. The parent and child pointers between x and x.parent are updated accordingly, and if x was previously the root node, the top node of R is the new root.

References

Worked examples

Example 1 — a first encounter with Zip tree

Start with the simplest possible case. Write down what Zip tree claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Zip tree before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Zip tree ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Zip tree

In research
Zip tree appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Zip tree in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Zip tree is common in secondary-school and first-year university syllabi. It links to neighbouring topics Binary trees, Search trees, so understanding it makes those chapters shorter.
In everyday life
Look for Zip tree outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Zip tree in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Zip tree means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Zip tree out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Zip tree in simple terms?

The zip tree was introduced as a variant of random binary search tree by Robert Tarjan, Caleb Levy, and Stephen Timmel. Zip trees are similar to max treaps except ranks are generated through a geometric distribution and maintain their max-heap property during insertions and deletions through unzipp…

Why does Zip tree matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Zip tree?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Zip tree.

Tags

  • Binary trees
  • Search trees

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