Sample
Dorn/cuda/40
Human rating uses the original dataset scale.
Scores
| Method | Score | Scale | Dataset rank (0–100) |
|---|---|---|---|
| Posnett | 0.611 | 0–1; higher is more readable | 83.0Δ 10.6 |
| Dorn | 0.172 | 0–1; higher is more readable | 13.1Δ 80.5 |
| Mi | 0.69 | 0–1; higher is more readable | 81.3Δ 12.3 |
| LLOC | 1 | Logical lines; fewer is more readable | 97.9Δ 4.3 |
| DeepSeek V4 Pro | 11.33 | 0–20; mean of three runs | 49.3Δ 44.3 |
| GPT-6.1 Sol | 18 | 0–20; mean of three runs | 93.5Δ 0.1 |
| BTTF | 0.53 | 0–1; higher is more readable | 53.5Δ 40.1 |
| Human | 4.07 | 1–5; original rating | 93.6 |
Views
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Source regions
Feature contributions
Feature contributions
| Feature | Value | Contribution (log-odds) |
|---|---|---|
| Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value. | 4.754 | −7.132 |
| Halstead volumeHow much symbolic information the code contains. It combines the total number of operators and values with the number of distinct ones. | 160.183 | −5.286 |
| Source linesThe number of non-empty source lines. | 10 | +4 |
Intercept 8.87 + feature contributions = 0.452 (log-odds).
Score = sigmoid(0.452) = 0.611.
Feature contributions
| Feature | Value | Contribution (log-odds) |
|---|---|---|
| Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *. | 0.411 | −3.053 |
| 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. | 35.909 | +2.144 |
| Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right. | 0 | −0.804 |
| Indentation frequencyHow rapidly indentation changes from line to line. | 1 | −0.703 |
| Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code. | 11 | +0.647 |
| Number layout frequencyHow rapidly the number of numeric values per line changes through the code. | 1 | +0.398 |
| Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom. | 9.784 | −0.273 |
Intercept 0.07 + feature contributions = -1.574 (log-odds).
Score = sigmoid(-1.574) = 0.172.
| Score | 0.69 |
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| Score | 1 |
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Run 1
The code fragment consists solely of preprocessor includes and a single macro definition. It is extremely short and flat, with no nesting or complex logic, which aids readability. However, clarity of intent is poor: the purpose of the included headers and the macro is not evident without surrounding code. The unused MAX_STEPS macro is ambiguous. Include directives are grouped logically (standard, CUDA utilities, custom header) but lack comments. Score reflects that while the snippet is easy to parse, it provides no meaningful structure or context to evaluate, and the missing code body limits actionable readability.
Run 2
This code is a minimal header/include block, not a functional implementation. Structure is flat and straightforward, but intent is completely unclear from the snippet. Missing headers like 'device_functions.h' and '_tt_backproject_ray_gpu.h' suggest hard dependencies and possible naming issues. The macro MAX_STEPS is defined but never used here. Overall, it reads like an orphaned fragment copied out of context.
Run 3
The code is a clean header inclusion block with a single macro definition. Structure is logical: standard C libraries first, then CUDA utilities, then a custom header. There is no nesting, and intent is clear—setting up dependencies for a CUDA-based ray backprojection program. Length is concise and appropriate. The macro MAX_STEPS is clearly defined with a large integer literal, though readability could be slightly improved by using a comment or a more descriptive constant name. Overall, the code is highly readable with no structural or flow issues.
Run 1
Code Structure: Includes are grouped before the constant definition, providing a logical organization. Nesting: There is no nesting. Clarity of intent: Header names suggest GPU ray backprojection, and MAX_STEPS identifies a step limit, but its unusually large value lacks explanation. Code length: The snippet is concise, though include necessity cannot be assessed without surrounding code. Action granularity: Each include and definition occupies its own line. Reading flow: The sequence is straightforward and easy to scan. This score reflects only the visible declarations, not the readability of the omitted implementation.
Run 2
Code Structure: Header inclusions followed by a constant definition form a simple, logical organization. Nesting: No nesting makes the snippet easy to scan. Clarity of intent: Dependencies are explicit, and MAX_STEPS is descriptive, although its unusually large value lacks explanation and the snippet does not reveal the broader program purpose. Code length: Very concise, with no obvious verbosity. Action granularity: Each include and definition occupies its own line. Reading flow: Standard headers precede CUDA-related and project headers, followed by the constant, creating a natural progression. Minor improvements would be grouping header categories with blank lines and explaining the limit.
Run 3
Code Structure: Includes are grouped before the constant definition, giving the snippet a simple, logical organization. Nesting: None, so there is no structural complexity. Clarity of intent: Header names suggest GPU ray backprojection, and MAX_STEPS communicates a step limit, but the purpose of the large value is unexplained. Code length: Very concise, with no obvious redundancy beyond minor extra whitespace. Action granularity: Each include and definition occupies its own line. Reading flow: Natural top-to-bottom setup, though separating standard, CUDA, and project headers would improve organization. This score applies only to the small setup snippet; no implementation is provided.