DFA Equivalence via Minimization and Isomorphism | Generated by AI
Question: Give some hints to solve problem 1671 “History of Languages” (determine if two DFAs accept the same language)
Answer:
Here are the most practical and commonly used hints/approaches to solve this problem efficiently:
Core Idea
Two DFAs accept the same language ⇔ their minimized versions are isomorphic (same number of states, same structure up to state renaming).
Since N ≤ 2000 per automaton and T ≤ 26, direct minimization + isomorphism check is feasible but needs to be implemented carefully.
Useful Hints & Strategies
- Handle dead/unreachable states first
- Many input DFAs contain unreachable states or states with no outgoing transitions.
- Run a DFS/BFS from state 0 on each DFA separately and only keep reachable states.
- This often reduces the effective number of states significantly.
- Treat missing transitions (−1) correctly
- The standard way is to create an explicit trap (dead) state.
- Add one extra state (say index N) that is:
- non-accepting
- transitions to itself on every symbol
- Replace every −1 transition with → this trap state.
- This makes the DFA complete (total transition function).
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Minimize each DFA (most important step) The standard efficient algorithm for your constraints is Hopcroft’s algorithm (O(|S| × |Σ| log |S|)), which is fast enough for N=2000, Σ=26.
Alternative (simpler to code but slower):
Use partition refinement with the basic table-filling / equivalence-class method:- Start with two groups: accepting vs non-accepting states
- Iteratively split groups until no more distinctions can be made
- Works well in practice for N ≤ 2000
- After minimization, check if the two minimal DFAs are isomorphic
- They must have the same number of states after minimization.
- There must exist a bijection between states that preserves:
- start state → start state
- accepting ↔ accepting
- transitions: δ₁(p,a) → q ⇔ δ₂(f(p),a) → f(q)
- You can do this by:
- Renumber states of one DFA starting from 0
- Try to build the mapping using BFS from the start states (state 0 of both)
- Check that the mapping is total, injective, and preserves transitions and acceptance
- Quick necessary (but not sufficient) checks (can early-reject)
- Same number of reachable states?
- Same number of accepting reachable states?
- Same number of states reachable in exactly k steps for small k?
- Same acceptance behavior on some random / short strings? (These are fast filters before doing full minimization.)
- Practical implementation order that works well
```
For each DFA:
- Read N, transitions, accepting flags
- Replace -1 → trap state (add state N if needed)
- Compute reachable states from 0 (BFS/DFS)
- Build the subgraph of only reachable states
- Minimize this DFA (Hopcroft or partition refinement)
- Get the number of states in minimal DFA + canonical state numbering
Finally:
- If number of states in min-DFA A ≠ min-DFA B → No
- Else try to check isomorphism by BFS-matching from start state ```
- Very useful observation for contest setting
- If both DFAs are already minimal and have ≤ 2000 states, isomorphism check alone is often enough.
- But in practice most test cases require minimization — many problems deliberately give non-minimal DFAs.
- Edge cases to watch for
- One or both automata accept nothing (only trap state reachable and non-accepting)
- One accepts everything (after minimization becomes 1 accepting state looping everywhere)
- Disconnected components (but you already filter unreachable)
- Start state not accepting vs accepting
- Empty string acceptance (check if state 0 is accepting)
Following steps 1–4 carefully (especially minimization + isomorphism) solves the problem correctly.
Good luck!
References:
- Hopcroft’s minimization algorithm explanation
- Standard way to check DFA equivalence via minimization