Sample

Dorn/cuda/82

Human rating uses the original dataset scale.

DatasetDorn
Human2.4
Lines30

Scores

MethodScoreScaleDataset rank
(0–100)
Posnett00–1; higher is more readable
3.1Δ 7.0
Dorn0.0330–1; higher is more readable
4.5Δ 5.6
Mi0.060–1; higher is more readable
8.6Δ 1.4
LLOC30Logical lines; fewer is more readable
11.4Δ 1.4
DeepSeek V4 Pro9.330–20; mean of three runs
37.2Δ 27.2
GPT-6.1 Sol11.330–20; mean of three runs
15.5Δ 5.4
BTTF0.1360–1; higher is more readable
2.8Δ 7.2
Human2.41–5; original rating
10.0

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Source regions

Feature contributions

Feature contributions

FeatureValueContribution
(log-odds)
Halstead volumeHow much symbolic information the code contains. It combines the total number of operators and values with the number of distinct ones.2898.958−95.666
Source linesThe number of non-empty source lines.30+12
Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value.3.863−5.795

Intercept 8.87 + feature contributions = -80.591 (log-odds).
Score = sigmoid(-80.591) = 0.

Feature contributions

FeatureValueContribution
(log-odds)
Identifier layout (horizontal)How rapidly the visual pattern of identifier characters changes from left to right. It measures spatial frequency, not the meaning of the names.107.968−0.908
Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right.0−0.804
Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *.0.171−0.719
Indentation frequencyHow rapidly indentation changes from line to line.1−0.703
Number layout frequencyHow rapidly the number of numeric values per line changes through the code.30−0.268
Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code.31−0.061
Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom.29.945+0.009

Intercept 0.07 + feature contributions = -3.384 (log-odds).
Score = sigmoid(-3.384) = 0.033.

Score0.06
Score30
Run 1

This code is mathematically dense but suffers from poor readability. The structure is disorganized with inconsistent variable naming (p000, p001, etc.) and no explanatory comments. The code is moderately nested but lacks clear intent - the trilinear interpolation and voxel accumulation operations are not obvious without domain knowledge. The action granularity is reasonable with one operation per line, but lines are extremely long due to verbose indexing expressions, hurting readability. The reading flow is poor - the algorithm's purpose is obscured by repetitive, similar-looking lines. Major issues include: repeated volumeVoxels indexing that could be extracted as a helper function or precomputed stride, magic numbers/conventions embedded in variable names, and lack of whitespace or comments to separate logical sections. The code would benefit significantly from a helper function to compute the flat index, better variable naming, and comments explaining the interpolation and splatting process.

Run 2

The code has a clear mathematical pattern (trilinear interpolation weights and voxel accumulation), but readability is significantly reduced by inconsistent formatting, poor variable naming, and repetitive index expressions. The structure is logically organized into weight computation and output assignment, but the lack of comments or helper functions obscures intent. Nesting is flat, which is positive, but each output line packs a full 3D index calculation into one line, violating granularity. Reading flow suffers from the odd initial alignment and subsequent misaligned continuations. The code could be much clearer with helper functions for voxel indexing, consistent spacing, and meaningful variable names.

Run 3

The code has a consistent pattern and is structured logically, but it suffers from severe readability issues due to excessive repetition, cryptic variable naming (p000, w000, etc.), and multiple operations packed into single lines. The trilinear interpolation weights and voxel index calculations are verbose and error-prone. While the flat structure is easy to follow, the dense indexing expressions and lack of abstraction make the intent hard to discern. Action granularity is mixed: some lines contain multiple assignments or a long expression, while others are simple. The reading flow is mechanical but not natural, as the reader must parse many similar formulas. Overall, it is understandable with effort but not highly readable.

Run 1

Code Structure: Coordinate preparation, weight calculation, and output accumulation form logical sequential groups, but repeated expressions obscure the organization. Nesting: The visible operations are flat; heavy indentation and an unmatched closing brace imply omitted surrounding structure. Clarity of intent: The eight weights suggest trilinear distribution into a voxel volume, but terse names and absent comments leave indexing conventions and synchronization purpose unclear. Code length: Explicitly expanding all eight cases makes the pattern visible but creates substantial repetition, especially in flattened-index calculations. Action granularity: Most lines perform one action, though the first three combine assignment and coordinate modification. Reading flow: Parallel weight and output statements are predictable, but dense arithmetic, inconsistent spacing, long lines, and the abrupt transition to synchronization and stepping reduce readability.

Run 2

Code Structure: Coordinate setup, weight calculation, and output accumulation form logical blocks, but repeated indexing expressions obscure organization. Nesting: The visible computations are flat, though heavy indentation and a closing brace indicate omitted surrounding structure. Clarity of intent: The eight weights suggest trilinear distribution across neighboring voxels, but terse names and no comments make the purpose harder to confirm. Code length: Explicitly listing eight cases is understandable, but repeated index calculations add verbosity. Action granularity: Most lines perform one action; the initial coordinate assignments combine assignment and mutation on single lines. Reading flow: The sequence from offsets to weights to accumulation is natural, but dense arithmetic, inconsistent spacing, and the abrupt transition to synchronization and stepping interrupt readability.

Run 3

Code Structure: The sequence logically computes offsets, interpolation weights, and output updates, but lacks clear section boundaries or helpers. Nesting: The visible calculations are flat, although heavy indentation and a closing brace suggest omitted enclosing logic. Clarity of intent: The eight-corner weighting pattern suggests trilinear distribution, but terse identifiers and unexplained indexing conventions require domain knowledge. Code length: Explicitly listing all eight cases is predictable but repetitive; repeated flattened-index expressions add unnecessary length. Action granularity: Most lines perform one assignment, but the initial lines combine copying and coordinate adjustment. Reading flow: Consistent ordering of weights and updates helps tracking, while long expressions, inconsistent spacing, and the abrupt transition to synchronization and position advancement hinder readability.