Not going to sugarcoat it, geometry problems are not my comfort zone.
Start by clarifying the problem and identifying the geometric primitives involved (points, lines, polygons, etc.). Then, reduce the problem to a known algorithmic pattern (e.g., sweep line, convex hull, divide and conquer) and discuss trade-offs between different approaches. Finally, outline a solution with clear time/space complexity and handle edge cases.
Pro tip: Verbalize your thought process and ask clarifying questions—interviewers value how you navigate ambiguity and structure a solution more than getting the optimal answer immediately. If stuck, simplify the problem (e.g., 1D or small cases) to gain insights.
Restate the problem in your own words and ask questions to clarify input/output formats, constraints, and edge cases (e.g., collinear points, duplicate points, large coordinates).
Determine which geometric primitives and relationships are relevant (e.g., orientation, intersection, distance, convexity) and how they map to algorithmic techniques.
Brainstorm multiple strategies (e.g., brute force, sweep line, divide and conquer, spatial indexing) and discuss their time/space complexities and trade-offs.
Select the most promising approach, detail the algorithm step-by-step, and optimize by handling edge cases and improving efficiency where possible.
Walk through small examples, including edge cases, to verify correctness and analyze complexity. Be prepared to code if asked.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by restating the problem and clarifying constraints, then propose a brute-force solution with its time complexity. Next, identify inefficiencies and optimize step-by-step, explaining how you achieve linear time complexity using appropriate data structures or algorithmic techniques. Finally, discuss trade-offs and test edge cases.
Pro tip: At Google, interviewers value clear communication and structured problem-solving over just getting the right answer. Verbalize your thought process and explicitly state the time and space complexity at each step.
Restate the problem in your own words, ask clarifying questions about input size, constraints, and edge cases, and confirm expected output.
Propose a straightforward solution, even if inefficient, and analyze its time and space complexity to establish a baseline.
Pinpoint the operations causing inefficiency (e.g., nested loops, repeated searches) and consider alternative data structures or algorithms.
Apply techniques like hash maps, two pointers, sliding window, or prefix sums to reduce complexity to O(n), explaining each step.
Walk through test cases including edge cases, verify correctness, and discuss space-time trade-offs and potential improvements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Prepped a bunch of structured situation-action-result examples beforehand and they held up.
Use the STAR method to structure your answers, focusing on specific situations where your values guided your actions, especially in ambiguous or conflict-laden scenarios. For hypotheticals, explicitly state your values and then walk through a logical decision-making process that aligns with those values.
Pro tip: Show self-awareness by acknowledging trade-offs and reflecting on what you learned, demonstrating that you continuously refine your values through experience.
Choose 2-3 values most relevant to the role and company, such as adaptability, collaboration, or integrity. Briefly explain why they matter to you.
Pick real examples from your past where you demonstrated these values, preferably in ambiguous or conflict situations. Use the STAR method to structure each story.
For hypothetical scenarios, state how you would apply your values to navigate the situation. Outline a step-by-step approach that shows your thought process.
Emphasize how you adjusted your approach when faced with ambiguity and how you resolved conflicts while staying true to your values.
Conclude by sharing what you learned from these experiences and how they shaped your values or approach to future challenges.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.