My first instinct was to just maintain an array of ball colors and update them each step, which works for step() but completely falls apart for color() in O(1).
First, clarify the problem: N positions in a circle, some marked, balls move clockwise one step per tick, starting white, and flip color when leaving a marked position. Then, design a data structure that maintains the count of white and black balls in O(1) per step, likely by tracking the color of each ball and updating counts incrementally. Finally, implement step() and color() accordingly, ensuring O(1) time for color() and O(1) per step for step().
Pro tip: Mention that the system is deterministic and periodic, so you can precompute the state cycle to answer color() in O(1) after initial setup, but for step() you still need O(1) per tick. Also, note that the number of marked positions affects the flip pattern, and you can optimize by only tracking balls that are about to leave marked positions.
Confirm the rules: balls move clockwise, flip when leaving a marked position, start white. Ask about initial configuration (number of marked positions, initial ball colors) and whether step() and color() need to be O(1) each or amortized.
Use an array to represent the circle, storing for each position whether it's marked and which ball is there (or just ball colors). Maintain a count of white and black balls. For O(1) step(), update only the balls that move from marked positions.
In each step, iterate over marked positions, flip the color of the ball leaving that position, update counts, and move all balls one step clockwise. To avoid O(N) per step, consider using a queue or circular buffer to track balls leaving marked positions.
Maintain white and black counts as instance variables, updating them during step(). color() simply returns these counts.
Discuss time complexity: step() should be O(1) per tick (or O(M) where M is number of marked positions, but M can be up to N). If M is large, consider precomputing the sequence of flips or using a more efficient simulation. Space complexity is O(N).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.