4 billion if statements (2023)

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

The three most prevalent themes in the discussion surrounding the article are:

Critique and Sarcasm Regarding Implementation Complexity vs. Simplicity: Many users pointed out that the highly complex, meta-programmed solution (generating 4 billion if statements) was an extreme over-engineering of a problem solved simply by looking at the last digit or using the modulo/bitwise AND operator.
- Supporting Quote: "All you need is the final binary digit, which incidentally is the most optimal codegen, v & 1." (mgaunard)
- Supporting Quote: "Horridly inefficient. Just unfold the loop." (kroolik)
The Sarcastic Praise of the "Visionary Genius": There was significant joking and sarcasm directed at the author's purported justification of using C due to "visionary genius" figures like Dennis Ritchie, often conflated with humorously incorrect attributions (like Ross van der Gussom for Python's creator).
- Supporting Quote: "Thanks for making me doubt myself & googling who that guy who made python was again, because surely 'van der Gussom' isn't a normal Dutch name. Well played." (isoprophlex)
- Supporting Quote: "I decided to use the slowest language on the planet, Python (thanks to the visionary genius of Ross van der Gussom)." (mbivert, quoting what they assume was the author's joke)
Discussion on Compiler Optimization and Performance: Users debated whether a compiler (like GCC) would simplify the absurd amount of code generated, or if disabling optimizations (as mentioned in the original experiment) was necessary to observe the intended effect, leading to further tests regarding compilation time.
- Supporting Quote: "Lets compile the code, disabling optimizations with /Od to make sure that the pesky compiler doesn’t interfere with our algorithm" (bspammer, quoting the likely practice)
- Supporting Quote: "Well I created the 16 bit .c file, because I'm not that curious. gcc -O0 completed immediately and made a 1,5MB executable. -O1 took about 10 minutes for a 1,8 MB executable. -O2 has been running for 1h15m so far..." (encom)

🚀 Project Ideas

Source Code Generator for Optimized C/C++ Lookups

Summary

A tool that takes a large set of conditional logic (like the 4B if-statement decision tree discussed) and automatically generates highly optimized source code using the least verbose, most performant structure available for the target language (e.g., switch statements with fall-through, table lookups, or optimized branching logic).
Solves the pain point of manually writing or metaprogramming verbose, repetitive conditional sequences that quickly become unmaintainable or result in bloated compilation artifacts.

Details

Key	Value
Target Audience	Developers facing massive, repetitive conditional logic in performance-critical C/C++ codebases (e.g., emulation, parsing, hardware drivers).
Core Feature	Converts pattern-based input (e.g., a range of numbers mapping to "even" or "odd") into optimized C syntax like sparse `switch` statements, array lookups, or bitwise operations, avoiding the excessive boilerplate seen in the discussion.
Tech Stack	Python (for generation logic), generating pure C/C++ code.
Difficulty	Medium

Notes

Why HN commenters would love it: Users expressed frustration with manually generating massive files of boilerplate (_ache_, PurpleRamen suggested generation). This tool automates the "meta-programming" aspect cleanly.
Potential for discussion or practical utility: This directly addresses the C++ template discussion and the desire for "data-driven programming" via array lookups (oneeyedpigeon), offering an automated bridge between data presentation and high-performance compiled output.

Byte-Size Lookup Pre-caching Service

Summary

A utility service that takes a definition mapping (e.g., the last digit/bit determines parity) and computes the entire necessary lookup table structure (e.g., an array or switch fall-through structure optimized for caching) specifically for assembly or C code generation, addressing the scale of the original problem set without runtime processing of the input number.
The core value proposition is providing ready-to-embed, static lookup structures that achieve database-like lookup speeds without the overhead of a runtime database connection.

Details

Key	Value
Target Audience	Systems programmers, embedded developers, or those needing extremely fast, localized lookups on large pre-calculated datasets (e.g., parity checks, CRC lookups).
Core Feature	Generates compiled-language structures (e.g., C header files containing massive static `const` arrays or hardcoded switch tables) based on the input problem constraints, making the decision instantly available at compile time.
Tech Stack	Go or Rust (for robust binary handling and fast compilation of generated output), generating C/C++ header files (`.h`).
Difficulty	Medium

Notes

Why HN commenters would love it: This addresses the performance concerns raised by wiz21c (local execution speed) and builds upon suggestions of using arrays/tables (oneeyedpigeon, d--b). It caters to the HN preference for compiled, zero-dependency solutions.
Potential for discussion or practical utility: It spawns debate on time-memory tradeoffs (actionfromafar) but provides a concrete output that maximizes performance for static determination problems.

Compiler Optimization Simulation Benchmarker

Summary

A platform that allows users to input C/C++ source code (like the 4B if statements) and simulate how modern compilers (GCC, Clang, MSVC) would optimize or prune that code at different optimization levels (e.g., checking what happens at -O0 vs -O3 vs /Od).
Solves the pain point of guessing how a compiler handles massive, repetitive structures, directly referencing the confusion over why the original code performed as it did despite disabled optimizations (bspammer, philippta).

Details

Key	Value
Target Audience	Performance researchers, compiler enthusiasts, and developers debugging unexpected behavior tied to optimization flags.
Core Feature	A sandbox environment for compiling and analyzing generated code across various compiler toolchains and flags, ideally providing disassembly output comparison or static analysis reports on branch complexity reduction.
Tech Stack	Docker/Containers (for isolated compiler environments), Web UI (React/Vue), Backend API (Node.js/Python).
Difficulty	High

Notes

Why HN commenters would love it: This directly addresses the meta-discussion about the compiler's role vs. the language's role (whynotmaybe, reedf1) and explains phenomena like code paging/caching (ricardo81) by letting users control optimizations explicitly.
Potential for discussion or practical utility: It fosters deep dives into compiler behavior, satisfying the technical curiosity that led to 469 comments in the first place.