Select next Hangman letter
Problem Statement
Implement a function to determine the optimal next letter to guess in a Hangman game. The function should select the letter with the highest likelihood of appearing in the secret word, based on the current game state and a provided dictionary.
Inputs
- Current Pattern String: A string representing the secret word's current state. Revealed letters are shown, while unknown letters are represented by a placeholder (e.g.,
_). - Guessed Letters Set: A collection of all letters that have already been guessed, including both correct and incorrect guesses.
- Dictionary: A list of valid words that could be the secret word.
Requirements
The function must perform the following steps:
- Identify Candidate Words: From the provided dictionary, filter down to a set of candidate words that are consistent with the current pattern string and do not contain any letters known to be absent (i.e., letters in the
Guessed Letters Setthat are not present in theCurrent Pattern String). - Calculate Letter Frequencies: Among the letters not yet guessed, determine the aggregate frequency of each letter across the identified set of candidate words.
- Select Next Letter: Choose the letter that maximizes this aggregate frequency.
- Deterministic Tie-Breaking: If multiple letters have the same maximal frequency, a deterministic policy must be specified and implemented to select one unique letter.
Deliverables
- A clear description of any preprocessing steps applied to the inputs.
- A detailed explanation of the algorithm.
- An analysis of the time and space complexity.
- Implementation of the function, including the deterministic tie-breaking policy.
AI interview prep
Core dilemma
Balancing the efficiency of filtering a potentially large dictionary against the accuracy of frequency calculation for the optimal next guess, while ensuring deterministic behavior and handling various game states.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Select next Hangman letter
Problem Statement
Implement a function to determine the optimal next letter to guess in a Hangman game. The function should select the letter with the highest likelihood of appearing in the secret word, based on the current game state and a provided dictionary.
Inputs
- Current Pattern String: A string representing the secret word's current state. Revealed letters are shown, while unknown letters are represented by a placeholder (e.g.,
_). - Guessed Letters Set: A collection of all letters that have already been guessed, including both correct and incorrect guesses.
- Dictionary: A list of valid words that could be the secret word.
Requirements
The function must perform the following steps:
- Identify Candidate Words: From the provided dictionary, filter down to a set of candidate words that are consistent with the current pattern string and do not contain any letters known to be absent (i.e., letters in the
Guessed Letters Setthat are not present in theCurrent Pattern String). - Calculate Letter Frequencies: Among the letters not yet guessed, determine the aggregate frequency of each letter across the identified set of candidate words.
- Select Next Letter: Choose the letter that maximizes this aggregate frequency.
- Deterministic Tie-Breaking: If multiple letters have the same maximal frequency, a deterministic policy must be specified and implemented to select one unique letter.
Deliverables
- A clear description of any preprocessing steps applied to the inputs.
- A detailed explanation of the algorithm.
- An analysis of the time and space complexity.
- Implementation of the function, including the deterministic tie-breaking policy.