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.

HardTechnical

38 practiced

Implement edit_distance(s, t) in Python computing Levenshtein distance (insert/delete/replace). Optimize space to O(min(n,m)) using rolling arrays, explain how to reconstruct an alignment path, and discuss optimizations for long sequences (e.g., Ukkonen's algorithm).

HardTechnical

39 practiced

You have ML pipeline tasks with dependencies. Implement topological_sort(tasks, deps) in Python using Kahn's algorithm to produce an execution order or raise an error if a cycle exists. Also discuss scheduling to maximize parallelism subject to resource constraints.

MediumTechnical

35 practiced

Implement top_k(stream, k) in Python that returns the k largest numbers seen in a potentially unbounded stream using O(k) memory. Provide code using heapq and discuss time/space complexity. Then explain how to adapt for top-k most frequent items (heavy hitters).

EasyTechnical

42 practiced

Describe how you'd write unit tests for a data preprocessing function normalize_and_fill(dataframe) that normalizes numerical columns and fills missing values. List edge cases and provide 3 pytest-style test examples (constant column, all-NaN column, extremely large values).

MediumTechnical

62 practiced

Implement Rabin-Karp substring search in Python: find all start indices where pattern occurs in text using a rolling hash. Discuss choice of base and modulus, collision handling, and average/worst-case complexity. Provide code-level details for the rolling computation.

Unlock Full Question Bank

Get access to hundreds of Coding Fundamentals and Problem Solving interview questions and detailed answers.

Join thousands of developers preparing for their dream job.