Do the file sizes and line counts of this repository follow Benford’s law?
research/benford-repo
Do this repository's file sizes follow Benford's law? Not as a whole (byte MAD 0.018, nonconforming) because templated files repeat the same size thousands of times; counting each distinct size once gives acceptable conformity (MAD 0.0068).
What it found
First-digit frequencies of the byte sizes and line counts of the 35,648 git-tracked files at one commit, scored against Benford’s law by chi-square and Nigrini’s mean absolute deviation (MAD). All files together are nonconforming (byte MAD 0.0183, line MAD 0.0278), because a few sizes repeat thousands of times (1,071 bytes 1,297 times, 47 bytes 993 times, 4 lines 1,822 times). Counting each distinct size once, byte sizes conform acceptably (MAD 0.0068, n = 12,429). By extension, .json and .html stay nonconforming even deduplicated, and distinct Python line counts are acceptable (MAD 0.0103, n = 476). Descriptive: one commit of one generated, templated repository; an illustration of when the law fails, not a test of the law.
Paper, code and results
More in Adversarial human imitation
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Other research topics
Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1
Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.