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Tree-walking automaton

Tree-walking automaton is a computer 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 Tree-walking automaton rather than just read about it. In short: A tree-walking automaton (TWA) is a type of finite automaton that deals with tree structures rather than strings. The concept was originally proposed by Aho and Ullman.

Key takeaways

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

Reference excerpt

A tree-walking automaton (TWA) is a type of finite automaton that deals with tree structures rather than strings. The concept was originally proposed by Aho and Ullman. The following article deals with tree-walking automata. For a different notion of tree automaton, closely related to regular tree languages, see branching automaton.

Definition All trees are assumed to be binary, with labels from a fixed alphabet Σ. Informally, a tree-walking automaton (TWA) A is a finite state device that walks over an input tree in a sequential manner. At each moment A visits a node v in state q. Depending on the state q, the label of the node v, and whether the node is the root, a left child, a right child or a leaf, A changes its state from q to q′ and moves to the parent of v or its left or right child. A TWA accepts a tree if it enters an accepting state, and rejects if its enters a rejecting state or makes an infinite loop. As with string automata, a TWA may be deterministic or nondeterministic. More formally, a (nondeterministic) tree-walking automaton over an alphabet Σ is a tuple A = (Q, Σ, I, F, R, δ) where Q is a finite set of states, its subsets I, F, and R are the sets of initial, accepting and rejecting states, respectively, and δ ⊆ (Q × { root, left, right, leaf } × Σ × { up, left, right } × Q) is the transition relation.

Example A simple example of a tree-walking automaton is a TWA that performs depth-first search (DFS) on the input tree. The automaton A {\displaystyle A} has three states, Q = { q 0 , q l e f t , q r i g h t } {\displaystyle Q=\{q_{0},q_{\mathit {left}},q_{\mathit {right}}\}} . A {\displaystyle A} begins in the root in state q 0 {\displaystyle q_{0}} and descends to the left subtree. Then it processes the tree recursively. Whenever A {\displaystyle A} enters a node v {\displaystyle v} in state q l e f t {\displaystyle q_{\mathit {left}}} , it means that the left subtree of v {\displaystyle v} has just been processed, so it proceeds to the right subtree of v {\displaystyle v} . If A {\displaystyle A} enters a node v {\displaystyle v} in state q r i g h t {\displaystyle q_{\mathit {right}}} , it means that the whole subtree with root v {\displaystyle v} has been processed and A {\displaystyle A} walks to the parent of v {\displaystyle v} and changes its state to q l e f t {\displaystyle q_{\mathit {left}}} or q r i g h t {\displaystyle q_{\mathit {right}}} , depending on whether v {\displaystyle v} is a left or right child.

Properties Unlike branching automata, tree-walking automata are difficult to analyze: even simple properties are nontrivial to prove. The following list summarizes some known facts related to TWA:

As shown by Bojańczyk and Colcombet, deterministic TWA are strictly weaker than nondeterministic ones ( D T W A ⊊ T W A {\displaystyle {\mathit {DTWA}}\subsetneq {\mathit {TWA}}} ) Deterministic TWA are closed under complementation (but it is not known whether the same holds for nondeterministic ones) The set of languages recognized by TWA is strictly contained in regular tree languages ( T W A ⊊ R E G {\displaystyle {\mathit {TWA}}\subsetneq {\mathit {REG}}} ), i.e. there exist regular languages that are not recognized by any tree-walking automaton, see Bojańczyk and Colcombet.

See also Pebble automata, an extension of tree-walking automata

References

External links Mikołaj Bojańczyk: Tree-walking automata. A brief survey.

Worked examples

Example 1 — a first encounter with Tree-walking automaton

Start with the simplest possible case. Write down what Tree-walking automaton claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer 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 Tree-walking automaton 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 Tree-walking automaton 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 Tree-walking automaton

In research
Tree-walking automaton appears in computer 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 Tree-walking automaton 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
Tree-walking automaton is common in secondary-school and first-year university syllabi. It links to neighbouring topics Automata (computation), Trees (data structures), so understanding it makes those chapters shorter.
In everyday life
Look for Tree-walking automaton 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 Tree-walking automaton in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Tree-walking automaton 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 Tree-walking automaton out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Tree-walking automaton in simple terms?

A tree-walking automaton (TWA) is a type of finite automaton that deals with tree structures rather than strings. The concept was originally proposed by Aho and Ullman.

Why does Tree-walking automaton matter?

Because it connects several computer 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 Tree-walking automaton?

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 Tree-walking automaton.

Tags

  • Automata (computation)
  • Trees (data structures)

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