Game Algorithms and Problem Solving Questions

Covers algorithmic and systems problems encountered in game development and real time simulation. Candidates should demonstrate how core computer science fundamentals map to practical gameplay and engine concerns, including pathfinding with A Star and related heuristics and optimizations, spatial partitioning and culling using structures such as quadtrees, octrees, and k dimensional trees, frustum culling, collision detection and response techniques including bounding volume hierarchies and continuous collision approaches, physics simulation approximations and numerical stability trade offs, particle systems, inventory and resource management, dialogue tree parsing, game state machines and transitions, efficient state serialization, snapshotting and delta compression, and networked game concerns such as latency compensation, synchronization, client authority versus server authority, interpolation and extrapolation. Assessment emphasizes algorithmic complexity and space and time trade offs, performance profiling and optimization for central processing unit and memory constrained environments, memory layout and cache friendliness, concurrency and multithreading strategies, deterministic simulation and lockstep architectures, debugging and testing deterministic systems, event driven designs, and designing maintainable engine or gameplay systems that balance correctness, responsiveness, scalability, and developer ergonomics. Candidates should be prepared to explain algorithms, analyze complexity, justify engineering trade offs, describe profiling methodology, and propose targeted optimizations to meet gameplay performance and scalability requirements.