Computer Science
Grade 12
20 min
Technical Interviews
Technical Interviews
Tutorial Preview
1
Introduction & Learning Objectives
Learning Objectives
Articulate a clear, step-by-step problem-solving process for algorithmic challenges.
Effectively communicate their thought process while coding a solution live.
Analyze and explain the time and space complexity (Big O notation) of their proposed solutions.
Develop and discuss multiple approaches to a problem, including brute-force and optimized solutions.
Ask clarifying questions to fully understand ambiguous problem statements and constraints.
Explain fundamental system design concepts and trade-offs.
Prepare and answer common behavioral questions using the STAR method.
Ever wondered how top tech companies decide who to hire? It's not just about your code, it's about how you think! ðŸ§
This lesson will equip you with the essential strategies...
2
Key Concepts & Vocabulary
TermDefinitionExample
Problem DecompositionThe process of breaking down a large, complex problem into smaller, more manageable, and solvable sub-problems.For the problem 'Find the longest palindromic substring,' you would first decompose it into a sub-problem: 'Write a helper function that checks if a given string is a palindrome.'
Think-Aloud ProtocolThe practice of verbalizing your thought process during an interview as you analyze, design, and code a solution.While solving a problem, you might say, 'My initial thought is a brute-force approach with nested loops, which would be O(n^2). I can probably optimize this by using a hash map to store previously seen values, which could get it down to O(n) time.'
Big O NotationA mathematical notation used to describ...
3
Core Syntax & Patterns
The REA Problem-Solving Framework
Repeat -> Examples -> Approach -> Code -> Test
A structured process for tackling any algorithmic problem. First, Repeat the problem back to the interviewer to ensure you understand it. Second, walk through concrete Examples to clarify requirements. Third, describe your high-level Approach (e.g., brute-force, then optimized). Fourth, write the Code. Finally, Test your code with your examples and edge cases.
Complexity Analysis Before Coding
State the Big O for time and space for every approach you suggest.
Before you write a single line of your final solution, you should state its time and space complexity and explain why it's an improvement over a more naive approach. This demonstrates that you prioritize performance and can...
4 more steps in this tutorial
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Challenging
You are given a complex graph problem and are unsure of the most optimal solution (e.g., Dijkstra's vs. Bellman-Ford). Based on the tutorial's principles, what is the best initial strategy?
A.Remain silent until you have figured out the perfect solution in your head.
B.Start by describing a simpler, more straightforward approach you are confident in, like a Breadth-First Search (BFS), analyze its limitations, and then use that as a starting point to discuss more complex possibilities.
C.Guess which of the optimal algorithms is correct and immediately start coding it.
D.Tell the interviewer the problem is too hard and ask for a different one.
Challenging
An interviewer asks you to 'Design a video streaming service.' Which clarifying question most effectively demonstrates your understanding of system design problem decomposition and trade-offs?
A.Which programming language should I use?
B.Should I focus on the front-end UI or the back-end architecture first?
C.What are the most critical features for the initial version, for example, are we prioritizing live streaming or video-on-demand, and what is the target scale of concurrent users?
D.How much time do I have to answer this question?
Challenging
You solve the 'Two Sum' problem with a hash map (O(n) time, O(n) space). The interviewer adds a new constraint: 'The input array is now guaranteed to be sorted.' How should you adapt your strategy to showcase advanced problem-solving skills?
A.State that the hash map is still the best solution.
B.Propose a new, more optimal solution using a two-pointer approach, which would have O(n) time and O(1) space complexity, and explain why it's now possible.
C.Use a binary search for each element, resulting in an O(n log n) time complexity.
D.Insist on coding the original hash map solution since you already planned it.
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