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Programming Languages & Core Development Topics

Programming languages, development fundamentals, coding concepts, and core data structures. Includes syntax, algorithms, memory management at a programming level, asynchronous patterns, and concurrency primitives. Also covers core data manipulation concepts like hashing, collections, error handling, and DOM manipulation for web development. Excludes tool-specific proficiency (see 'Tools, Frameworks & Implementation Proficiency').

C and C++ Programming

The C and C++ languages: syntax and semantics, the type system, the standard library and STL, templates, RAII, and idiomatic modern C++. Covers writing correct code and reasoning about the language features that distinguish these systems languages from managed ones. A primary language surface for systems, game, and embedded interviews.

0 questions

Functional Programming

Functional-style programming: pure functions, immutability, higher-order functions, closures, currying and partial application, and memoization, along with functional reactive patterns. Covers reasoning about code as composed transformations rather than mutable state, whether in a dedicated functional language or a multi-paradigm one. Increasingly probed for frontend and data-heavy work.

0 questions

Language-Level Concurrency and Multithreading

Per-language and per-runtime concurrency: the threading and async APIs each language provides (goroutines and channels in Go, threads and executors in Java, async/await runtimes, C++ std::thread and atomics), each language's memory model, and the idioms for coordinating shared state safely in that language. Covers choosing and using a language's concurrency primitives correctly; OS-level scheduling, synchronization theory, and deadlock internals live in Operating Systems & Systems Programming.

0 questions

Programming Fundamentals

Language-agnostic building blocks of writing code: variables, primitive and composite data types, scope and lifetime, functions and callbacks, control flow, and expressions versus statements. Covers the mental model a candidate needs before any language-specific or algorithmic depth. The baseline literacy layer of a technical screen.

12 questions

Error Handling and Defensive Programming

Making code robust against bad input and failure: exceptions versus error returns, input validation, guard clauses, graceful degradation, and designing for the unhappy path. Covers where to handle versus propagate errors and how to fail safely without hiding bugs. A recurring probe of production maturity.

0 questions

Assembly and Low-Level Language Fundamentals

Programming at or near the instruction level: assembly syntax, registers, the stack, calling conventions, and translating higher-level code down to machine operations. Covers reasoning about how source constructs map to CPU instructions. A niche but high-signal surface for embedded, systems, and security work.

30 questions

Language-Level Memory Management (C/C++/Rust)

How specific languages expose and manage memory: pointers and references, pointer arithmetic, stack versus heap allocation, ownership and borrowing in Rust, RAII and smart pointers in C++, manual allocation and freeing in C, and garbage-collection semantics as a language feature. Covers reasoning about ownership, lifetimes, leaks, and dangling references at the language level. OS-level virtual memory and paging internals live in Operating Systems & Systems Programming.

80 questions

Shell Scripting and Automation

Automating tasks with the command line: Bash and shell scripting, pipes and redirection, text processing, and writing custom tooling and monitoring scripts to glue systems together. Covers the scripting fundamentals infrastructure and platform engineers use daily, including automation-oriented use of general-purpose scripting. Distinct from application programming in its throwaway-to-durable tooling mindset.

30 questions

Clean Code, Refactoring, and Maintainability

Writing code that other people can read, change, and keep alive over time: naming, function and module decomposition, avoiding duplication, readability, disciplined use of language idioms and design patterns, and recognizing code smells, extending into working effectively in large, aging, or unfamiliar codebases through safe incremental change, refactoring under test coverage, and managing technical debt. Covers both authoring professional-grade code beyond mere correctness and improving code you cannot rewrite without breaking it. Spans the coding-round quality signal and the seniority signal of leaving a codebase healthier than you found it.

0 questions
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