Coding Fundamentals and Problem Solving Questions

Focuses on algorithmic thinking, data structures, and the process of solving coding problems under time constraints. Topics include core data structures such as arrays, linked lists, hash tables, trees, and graphs, common algorithms for searching and sorting, basics of dynamic programming and graph traversal, complexity analysis for time and space, and standard coding patterns. Emphasis on a disciplined problem solving approach: understanding the problem, identifying edge cases, proposing solutions with trade offs, implementing clean and readable code, and testing or reasoning about correctness and performance. Includes debugging strategies, writing maintainable code, and practicing medium difficulty interview style problems.

MediumTechnical

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Describe common race conditions and deadlock scenarios in multi-threaded code. Give examples of how you would detect, reproduce, and fix them, and list tools and strategies (sanitizers, deterministic replay, stress testing) you would recommend for a high-throughput service.

MediumTechnical

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Implement in Python a function that given an unsorted list of integers and a target returns indices of the two numbers that add up to the target. Your solution should run in O(n) time using O(n) extra space. Explain trade-offs versus a sort-and-two-pointer O(n log n) approach and how you would test at scale.

MediumTechnical

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Compare adjacency list and adjacency matrix graph representations detailing memory usage, speed of common operations like edge existence checks and iteration, sparsity considerations, and how representation choice influences algorithm selection for large-scale graph processing.

HardTechnical

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You are shown the following Python function that attempts to compute the top-k frequent words from a list but produces nondeterministic or incorrect results when tie counts occur. Identify the bug, propose a fix, and describe unit tests you would add. Function: def top_k(words,k): counts = {} for w in words: counts[w] = counts.get(w,0)+1 return sorted(counts.items(), key=lambda x: x[1], reverse=True)[:k]

EasyTechnical

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How do you define and enforce coding standards and code review practices across multiple engineering teams as a solutions architect so that code remains maintainable, readable, and secure? Provide concrete examples of tools, process changes, and measurable metrics you'd use to evaluate adoption.

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