Programming Fundamentals and Code Quality Questions

Encompasses core programming skills, data structures, basic algorithms, language fundamentals, and code quality practices. Expect proficiency with arrays, strings, lists, hash maps or dictionaries, sets, common collection operations, basic sorting and searching algorithms, and tradeoffs between data structures. Understand control flow, functions and modular design, classes and object oriented programming concepts including encapsulation, inheritance, and polymorphism, exception handling, file input and output, and common language idioms for mainstream interview languages such as Python, Java, and C plus plus. Emphasizes writing clean, readable, maintainable code: meaningful naming, modular functions, small interfaces, handling edge cases and errors, logging and documentation, simple testing and debugging strategies, and awareness of time and space complexity for common operations. Candidates should be able to implement correct solutions, follow language specific idioms where appropriate, and demonstrate attention to code quality and readability.

EasyTechnical

28 practiced

Explain the average and worst-case time complexity of common dictionary operations in Python such as lookup, insert and delete. Describe one scenario where a hash table degenerates and how Python mitigates that risk.

HardTechnical

30 practiced

Write production-quality Python code to safely deserialize a user-provided JSON string into native objects. Address security concerns, unexpected types, and how you would validate and sanitize fields before using them in downstream code like SQL queries or file paths.

MediumTechnical

34 practiced

Given a CSV with a 'timestamp' and multiple numeric feature columns too large to fit in memory, describe an approach for computing per-feature streaming mean and variance in a single pass with constant memory. Provide formulas and a short code sketch for online updates.

MediumTechnical

26 practiced

Implement a function in Python to find the longest substring without repeating characters. State complexity and explain how your sliding window or two-pointer approach works. Discuss how your approach performs on very long strings and memory tradeoffs when storing indices.

HardTechnical

28 practiced

Implement a stable in-place partition function in C++ that partitions an array around a pivot value preserving relative order of equal elements. Explain challenges with in-place stability and provide complexity analysis. Discuss use cases in data pipelines where stable partitioning matters.

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