Sample

Scalabrio71

Human rating uses the original dataset scale.

DatasetScalabrino
Human3.56
Lines41

Scores

MethodScoreScaleDataset rank
(0–100)
Posnett00–1; higher is more readable
18.6Δ 26.9
Scalabrino0.3640–1; higher is more readable
30.7Δ 14.8
Dorn0.0640–1; higher is more readable
12.1Δ 33.4
Mi0.0140–1; higher is more readable
8.0Δ 37.4
LLOC25Logical lines; fewer is more readable
11.8Δ 33.7
DeepSeek V4 Pro7.670–20; mean of three runs
9.5Δ 35.9
GPT-6.1 Sol150–20; mean of three runs
19.6Δ 25.9
BTTF0.3680–1; higher is more readable
9.5Δ 35.9
Human3.561–5; original rating
45.5

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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.1482.365−48.918
Source linesThe number of non-empty source lines.41+16.4
Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value.4.904−7.356

Intercept 8.87 + feature contributions = -31.004 (log-odds).
Score = sigmoid(-31.004) = 0.

Score0.364

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.207.902−5.141
Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right.208+2.551
Indentation frequencyHow rapidly indentation changes from line to line.39+0.612
Number layout frequencyHow rapidly the number of numeric values per line changes through the code.39−0.474
Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code.41−0.415
Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom.39.775+0.146
Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *.0.1−0.032

Intercept 0.07 + feature contributions = -2.682 (log-odds).
Score = sigmoid(-2.682) = 0.064.

Score0.014
Score25
Run 1

The code is a test method that performs database operations and assertions but suffers from poor readability due to mixed indentation (tabs and spaces), inconsistent spacing, and multiple actions per line in some areas. The structure is somewhat logical but the flow is interrupted by style inconsistencies and the long SQL query strings. Nesting is shallow, which is good, but the intent is partially obscured by the abrupt session handling and dialect-specific branching. Action granularity is moderate; some lines combine multiple actions. Code length is acceptable, but readability is significantly reduced by formatting and unclear variable naming. Overall, the code is understandable but requires effort to parse visually.

Run 2

The code has poor readability. It mixes multiple responsibilities in one method (delete, save, query, dialect-specific logic), making the intent hard to follow. The indentation is inconsistent, especially in the if-else block, which disrupts reading flow. Nesting is shallow but the method is long and the logic is tangled. Variable names like 'A', 'B', 'TA', 'count_' are unclear, reducing clarity of intent. Multiple operations occur per block without separation (e.g., commit and close in one line). The dialect-specific SQL adds complexity and is not well-commented. Overall, the code needs refactoring into smaller methods with meaningful names and consistent formatting to improve readability.

Run 3

The code has several readability issues. Structure is somewhat organized but the test method contains too many responsibilities: session management, entity cleanup, data setup, and query testing. Nesting is minimal except for the dialect conditional, which is a positive. Intent is partially clear but muddled by comments that explain workarounds rather than the core logic. Code length is excessive for what is being tested — session handling and cleanup could be extracted. Action granularity varies: some lines combine multiple operations, while others are appropriately single-purpose. Reading flow suffers due to inconsistent indentation (tabs vs spaces), long query strings, and the interrupted logic flow between setup and assertion. Naming is adequate but not descriptive enough to reveal intent quickly. Overall, the code achieves its purpose but requires effort to understand.

Run 1

Code Structure: The test logically progresses through cleanup, data setup, query execution, and assertions, but repeated session lifecycle code adds clutter. Nesting: Shallow, with only a loop and a simple dialect-specific conditional. Clarity of intent: The test name, assertions, and TimesTen comment communicate its purpose, though the unused count variable and unexplained B entity distract. Code length: Reasonably short, but duplicated SQL and transaction handling make it longer than necessary. Action granularity: Most statements perform one action per line; chained query calls remain understandable. Reading flow: Execution follows a natural sequence, but inconsistent indentation and spacing, raw List usage, and long SQL lines interrupt scanning.

Run 2

Code Structure: Logically separates data setup, query execution, and assertions, though repeated session management adds clutter. Nesting: Shallow, with only a loop and a simple dialect conditional. Clarity of intent: The test name, assertions, and TimesTen comment explain the purpose, but the unused count variable and unexplained B entity distract. Code length: Generally manageable, although duplicated long SQL strings and repeated transaction handling reduce conciseness. Action granularity: Most lines perform one action; query-building chains remain understandable. Reading flow: Execution proceeds naturally from setup to verification, but inconsistent indentation and spacing, long SQL lines, and generic names such as query and list slightly hinder readability.

Run 3

Code Structure: Clearly separates data setup from query execution and assertions, although repeated session lifecycle code and duplicated SQL reduce organization. Nesting: Shallow, with only a cleanup loop and a simple dialect-specific conditional. Clarity of intent: The test name, assertions, and TimesTen comment explain the purpose, but single-letter entity names, a raw List, and the unused count variable add ambiguity. Code length: Reasonable for an integration test, though the unused query and repeated SQL make it longer than necessary. Action granularity: Most statements perform one action per line; fluent query construction remains understandable. Reading flow: Execution follows a natural setup-test-verify sequence, but inconsistent indentation and spacing, long SQL strings, and repeated transaction handling interrupt readability.