Google Wordle Feedback Validation

Learning Outcome

Turn the Google Wordle Feedback Validation interview variant into a clear brute-force baseline, optimized pattern, and implementation plan.

Original Interview Statement

Given guess1 and its color feedback, decide whether another candidate secret is consistent with that feedback.

Examples

Brute Force Approach

Try to manually convert colors into many separate constraints; duplicate letters make this fragile.

Optimized Approach

A candidate is valid exactly when running the original feedback algorithm with candidate as secret reproduces the known color string.

Exact Pseudocode

return color(candidateSecret, guess1) == knownColor
  

Reference Code

def feedback(secret, guess):
    from collections import Counter
    ans = ['b'] * len(secret)
    left = Counter()
    for i, (s, g) in enumerate(zip(secret, guess)):
        if s == g:
            ans[i] = 'g'
        else:
            left[s] += 1
    for i, g in enumerate(guess):
        if ans[i] == 'g':
            continue
        if left[g] > 0:
            ans[i] = 'y'
            left[g] -= 1
    return ''.join(ans)

def is_valid_candidate(guess1, color1, candidate_secret):
    return feedback(candidate_secret, guess1) == color1
  

Complexity

Edge Cases

• Repeated letters with both yellow and black
• Green positions
• Candidate length mismatch

Follow-ups

• Validate against multiple previous guesses
• Generate any possible secret

Nearest Practice References

• Wordle
• Mastermind consistency

Common Mistakes

• Copying the nearest LeetCode solution without checking the changed rule.
• Skipping duplicate or boundary cases.
• Not stating the brute force before the optimized approach.