Most Influential Papers in Computer Science History

Overall reaction to the list

• Many commenters felt the list was “legit” and captured genuinely foundational work.
• Others noted it’s inherently incomplete: two web papers but nothing from graphics, OS, GUIs, or several other major subfields.
• Some found the mix of theoretical foundations and very applied/industry-shaping work a bit incoherent and wished the criteria (science vs technology vs “all things computer”) were clearer.

Reading and understanding classic papers

• Several classics (computability, NP-completeness) are reported as very hard to follow; people recommend auxiliary books, lecture notes, or annotated editions.
• One suggestion: if LaTeX sources exist, regenerate them with clearer, longer variable names.
• The foundational information theory paper is praised as beautifully written but non‑casual reading.
• The PageRank and relational model papers are remembered as comparatively approachable, though the former’s full justification benefits from linear algebra or fixed‑point perspectives.

Debate over specific inclusions (e.g., PageRank, networking)

• Some feel PageRank is too domain-specific to stand beside deep theoretical work; others argue it deeply shaped the modern web and illustrates important ideas in ranking, Markov chains, and iterative methods.
• The IP paper is seen as technologically central but “just” a protocol spec rather than deep science.
• There is curiosity about long‑term relevance: foundational theory papers seem timeless, whereas PageRank’s future importance is questioned.

Missing domains and suggested additions

• Cryptography: strong sentiment that seminal public‑key and secrecy‑systems papers, plus work on modern techniques (FHE, MPC, ZK), should appear.
• Systems and OS: Unix, time-sharing evolution, virtual synchrony, MapReduce, file systems, rsync, relational query language design, and module decomposition are all proposed.
• Distributed algorithms: consensus and clock/ordering papers, Byzantine generals, actor formalism, and practical consensus variants are emphasized; some skepticism exists about their real‑world deployment, countered by reports of extensive use.
• Theory/PL/SE: lambda calculus, Lisp, structured programming critiques, CSP, “next 700 languages,” non‑von‑Neumann programming, and proof/logic systems are repeatedly mentioned.
• ML/AI: backpropagation, early neural models, convolutional breakthroughs, and the attention/Transformer paper are all argued as transformative.

Bitcoin, blockchains, and impact

• Some argue the Bitcoin paper deserves inclusion because it spawned a huge economic ecosystem and advances in trustless distributed computing.
• Others rebut that it mainly combines prior ideas, adds little to core CS, and that underlying cryptographic and consensus work is more fundamental.

Clarifications and meta-discussion

• There is correction of common misunderstandings about what the computability/decision-problem paper actually proves versus the broader thesis about “what is computable.”
• A side thread debates whether models like actors are “more powerful” than Turing machines, with responses pointing to nondeterministic Turing machines and the distinction between descriptive formalisms and effective computation.
• Another subthread raises the absence of women‑authored papers; replies split between defending purely “merit/impact”-based selection and arguing that some omitted work is at least as influential as much of the list.