Computer Science Roadmap¶

• Roadmap: https://roadmap.sh/computer-science

This roadmap is the senior / staff deep-dive layer of computer science: how each layer works internally and why — the bar that separates senior/staff engineers from "knows how to use it." The roadmap.sh intro topics that overlap with other roadmaps in this repo are not re-authored here (see Foundations below); they live at their authoritative home. Each subtopic here is a skeleton folder, content TBD.

Deep-Dive Sections (bottom-up)¶

Ordered foundations → applied, each layer building on the one before it.

1. Discrete Mathematics — logic & proofs, set theory, combinatorics, probability, graph theory, number theory, recurrences, boolean algebra (the math under algorithm analysis & complexity)
2. Theory of Computation — automata, context-free grammars, Turing machines/computability, halting problem, P vs NP/NP-completeness, reductions
3. Information Theory — entropy/Shannon, compression (Huffman/LZ77), error-correcting codes
4. Computer Architecture — pipelining/OOO, branch prediction, cache coherence (MESI), TLB, NUMA, memory ordering, SIMD, mechanical sympathy
5. Operating Systems — scheduler internals, virtual memory, page replacement, IPC, I/O models (epoll/io_uring), context switching, interrupts, real-time
6. Concurrency & Parallelism — memory models, happens-before, atomics/CAS, lock-free/wait-free, Amdahl/USL, race conditions/ABA, actor/CSP
7. Networking Internals — TCP congestion/flow control, HOL blocking, TLS 1.3 handshake, QUIC/HTTP3, L4 vs L7 LB, latency numbers, DNS/anycast, network namespaces
8. Compilers & Language Theory — lexing/parsing, AST/semantic analysis, IR/SSA, optimization passes, codegen, JIT vs AOT, garbage collection
9. Database Internals — LSM vs B-tree storage, MVCC, WAL/recovery, query planner, consensus (Raft/Paxos), CRDTs/vector clocks, distributed transactions
10. Distributed Systems Theory — CAP/PACELC, FLP impossibility, consistency models, logical/vector clocks, quorums/gossip, consensus foundations
11. Cryptography & Security — symmetric (AES), asymmetric (RSA/ECC), hash/KDFs, TLS/PKI internals, zero-knowledge proofs, side-channel attacks
12. Programming Language Theory — lambda calculus, operational/denotational semantics, type systems & inference (Hindley-Milner), polymorphism/subtyping, effects/monads, dependent & refinement types
13. GPU & Parallel Computing — GPU architecture & execution model, CUDA/GPGPU, memory coalescing, parallel primitives (scan/reduce), parallel algorithm design, graphics rendering pipeline
14. Numerical Methods & Scientific Computing — floating-point error analysis, numerical stability/conditioning, linear solvers & decompositions, iterative methods, FFT/spectral methods, numerical integration & ODEs

Companion roadmaps: - Data Structures & Algorithms — algorithmic foundations - System Design — applying CS at the architecture level - Databases — vendor-agnostic database concepts

Foundations — covered in their canonical roadmaps¶

The roadmap.sh "computer science" intro repeats material that already lives — more thoroughly — in other roadmaps in this repo. To avoid duplication, those topics are not re-authored here; learn them at their authoritative home: