The holistic discipline of computer science: from foundational divide-and-conquer algorithms and data structures to CPU architecture, operating system kernels, compilers, and distributed consensus networks.
Divide-and-conquer, greedy heuristics, dynamic programming, shortest-path graph traversals, Big-O asymptotic analysis, and quantum algorithms.
Linear arrays, linked lists, self-balancing BSTs (AVL/Red-Black), B-Trees, heaps, hash tables, tries, and cache-friendly memory layouts.
CPU instruction pipelines, register sets (x86/ARM/RISC-V), memory hierarchy, cache coherence, MMU virtual memory paging, and hardware logic.
Kernel space vs user space, process scheduling, multithreading, mutexes/semaphores, virtual file systems, interrupt handlers, and syscalls.
Lexical analysis, AST generation, semantic analysis, type systems, intermediate representation (IR), LLVM optimization, and bytecode VMs.
CAP theorem, leader election, Raft and Paxos consensus, distributed hash tables, RPC protocols, replication, and fault tolerance at scale.