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').
Concurrency and Synchronization
Covers the principles and practical techniques for safely coordinating concurrent execution and access to shared resources. Topics include models of concurrency such as threads, processes, interrupt handlers, and tasks in a real time operating system; differences between preemptive and cooperative scheduling; shared data hazards including race conditions and read modify write hazards; critical sections and approaches to protect them including disabling interrupts in embedded contexts and scoped locks. Synchronization primitives and patterns are included: mutexes, binary semaphores, counting semaphores, condition variables, message queues, atomic operations and lock free primitives such as compare and swap. Memory ordering concerns and memory barrier usage on multi core systems are covered, along with priority inversion and priority inheritance. Also addressed are deadlock, livelock, and starvation concepts and avoidance strategies, granularity and performance trade offs of locking, and practical synchronization patterns. Preparation should include identifying and fixing races in code, designing correct concurrent interfaces, and debugging and testing techniques such as stress testing, instrumentation, deterministic replay, race detectors, static analysis, and code review strategies.
Systems Programming & Low-Level Concepts
Systems programming concepts including memory management, pointers, memory layout, CPU architecture considerations, concurrency primitives, OS interactions, and performance optimization in low-level languages (C, C++). Covers how languages expose low-level resources, toolchains, and platform-specific behaviors; excludes high-level application development.
Error Handling and Code Quality
Focuses on writing production quality code and scripts that are defensive, maintainable, and fail gracefully. Covers anticipating and handling failures such as exceptions, missing files, network errors, and process exit codes; using language specific constructs for error control for example try except blocks in Python or set minus e patterns in shell scripts; validating inputs; producing clear error messages and logs; and avoiding common pitfalls that lead to silent failures. Also includes code quality best practices such as readable naming and code structure, using standard libraries instead of reinventing functionality, writing testable code and unit tests, and designing for maintainability and observability.
Error Handling and Defensive Programming
Covers designing and implementing defensive, fault tolerant code and system behaviors to prevent and mitigate production failures. Topics include input validation and sanitization, null and missing data handling, overflow and boundary protections, exception handling and propagation patterns, clear error reporting and structured logging for observability, graceful degradation and fallback strategies, retry and backoff policies and idempotency for safe retries. Also address concurrency and synchronization concerns, resource and memory management to avoid exhaustion, security related input checks, and how to document and escalate residual risks. Candidates should discuss pragmatic trade offs between robustness and complexity, show concrete defensive checks and assertions, and describe test strategies for error paths including unit tests and integration tests and how monitoring and operational responses tie into robustness.
Network Programming and Scripting Proficiency
Show practical programming and automation skills focused on networking tasks, using languages such as Python, Go, or shell scripting. Topics include socket programming and protocol knowledge for TCP and UDP, HTTP and higher level APIs, automation of network devices and cloud platform APIs, use of client libraries and remote management protocols, writing maintainable scripts and tools with error handling and retries, testing and validation of network code, performance and scaling considerations for scripts and agents, debugging and logging strategies, and code review and collaboration practices for operational tooling. Candidates should be able to discuss examples of network automation, tooling, monitoring integrations, and how they handled reliability and performance trade offs.
Maintainability and Legacy Code
Covers strategies and principles for evolving codebases safely and keeping them easy to understand and change over time. Topics include design principles such as Single Responsibility, Open Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion, removing duplication, establishing appropriate abstraction boundaries, separation of concerns, identifying and remediating code smells, incremental refactoring approaches, regression risk mitigation via tests and feature toggles, backward compatibility and migration strategies, and prioritizing technical debt reduction. Interviewers assess the candidate ability to plan pragmatic refactors, minimize risk during change, and improve long term health of a codebase.
Core Data Structures
Fundamental built in data structures used in everyday programming and coding interviews, focusing on lists, strings, and dictionaries. For lists cover indexing, slicing, iteration, common mutation operations such as append and extend, common algorithms such as sorting and reversing, and memory and performance implications. For strings cover indexing, slicing, common methods such as split, join, strip, replace, and approaches to string manipulation and pattern processing. For dictionaries cover key value semantics, insertion and lookup, iteration patterns, methods for safe access, and using dictionaries as hash tables for counting and grouping. Candidates should also know the time complexity of common operations expressed in plain terms such as constant time, linear time, and quadratic time, and be able to choose the appropriate structure for a problem and reason about space and performance tradeoffs. Practice often includes implementation level manipulations, common interview problems such as two sum and frequency counting, and writing clear code using these structures.
Advanced Data Structures and Implementation
Deep and practical expertise in advanced data structures, their implementation details, performance characteristics, and selection for both algorithmic problems and production systems. Topics include arrays and dynamic arrays, strings, linked lists, stacks and queues, hash tables, heaps and priority queues, various tree forms including binary search trees and balanced trees, tries or prefix trees, segment trees and binary indexed trees or fenwick trees, union find or disjoint set union, suffix arrays, and advanced graph representations. Candidates should be able to implement core structures from first principles, demonstrate interfaces and invariants, reason about insertion deletion search traversal and iteration costs including worst case average case and amortized analysis, and discuss memory management and ownership in low level languages such as C and C plus plus as well as safe memory and reference use in managed languages. Evaluation also covers trade offs between contiguous and pointer based layouts, cache friendliness, concurrency considerations, selection of structures based on access patterns update frequency and memory constraints, handling of edge cases, testing and performance tuning for realistic inputs, and applying structures to problems such as top K queries prefix search connectivity range queries caches and union operations.
Backend Language Proficiency
Demonstrate strong practical knowledge of a backend programming language such as JavaScript with Node dot js, Python, Java, Go, or similar. Cover language fundamentals, idiomatic usage, standard library features, package and dependency management, common frameworks and ecosystem tools, testing strategies and tooling, error handling and observability, and patterns for maintainable server side code. Be ready to explain concurrency and asynchronous models in the language, performance considerations, security best practices, deployment and packaging approaches, and examples of backend services or APIs you built including trade offs and chosen libraries.