Sample

Scalabrio199

Human rating uses the original dataset scale.

DatasetScalabrino
Human3.67
Lines11

Scores

MethodScoreScaleDataset rank
(0–100)
Posnett0.3540–1; higher is more readable
88.9Δ 35.9
Scalabrino0.6310–1; higher is more readable
62.8Δ 9.8
Dorn0.2580–1; higher is more readable
33.7Δ 19.3
Mi0.1930–1; higher is more readable
46.2Δ 6.8
LLOC2Logical lines; fewer is more readable
98.7Δ 45.7
DeepSeek V4 Pro70–20; mean of three runs
7.8Δ 45.2
GPT-6.1 Sol14.670–20; mean of three runs
13.8Δ 39.2
BTTF0.5570–1; higher is more readable
58.3Δ 5.3
Human3.671–5; original rating
53.0

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Source regions

Feature contributions

Feature contributions

FeatureValueContribution
(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.4.834−7.251
Halstead volumeHow much symbolic information the code contains. It combines the total number of operators and values with the number of distinct ones.200.674−6.622
Source linesThe number of non-empty source lines.11+4.4

Intercept 8.87 + feature contributions = -0.604 (log-odds).
Score = sigmoid(-0.604) = 0.354.

Score0.631

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.111−1.036
Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code.1+1.001
Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right.0−0.804
Number layout frequencyHow rapidly the number of numeric values per line changes through the code.1+0.398
Indentation frequencyHow rapidly indentation changes from line to line.11−0.357
Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom.9.812−0.273
Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *.0.103−0.056

Intercept 0.07 + feature contributions = -1.057 (log-odds).
Score = sigmoid(-1.057) = 0.258.

Score0.193
Score2
Run 1

The code is functionally correct but has readability issues. The nesting is deep and the assertion spans many lines due to chained method calls and line breaks, making it hard to follow. Intent is somewhat clear (testing a column name), but the action granularity is poor because multiple operations are packed into one line. The reading flow is disrupted by the long cast and iterator chain. Better structure would extract the column name into a local variable first.

Run 2

The code is a single test method with one assertion, but readability is poor due to excessive nesting and unclear intent. The assertion chains multiple calls across several lines, making it difficult to follow the logic at a glance. The use of line breaks splits a single logical operation into many fragments, which breaks reading flow. The method name suggests it tests a child ID column name, but the actual value being validated ('other_id') is buried deep within the expression. The structure is tangled, with high line count for one action. Improving readability would involve extracting intermediate variables or using a helper method to isolate the column retrieval, then asserting on the result. Overall, it is functional but not concise or naturally readable.

Run 3

The code suffers from severe readability issues. The single assertion is heavily nested with method chaining, making it difficult to follow. It violates the 'one action per line' principle by combining multiple operations (getClassMapping, getKey, getColumnIterator, next, getName) in one chain. The intent is unclear without deep understanding of the domain. The formatting, with excessive indentation and scattered parentheses, disrupts natural reading flow. While it is concise, conciseness here harms clarity. The deep nesting of method calls and unclear line breaks make it very hard to parse. A better approach would be to extract the column retrieval into separate variables and format the assertion more clearly.

Run 1

Code Structure: A logically organized, single-purpose test, though configuration lookup and casting are embedded in the assertion. Nesting: No nested control flow, but the cast, method chain, and assertion create moderately nested expressions. Clarity of intent: The test name and expected value clearly indicate a child ID column-name check; the long class name and iterator access add parsing effort. Code length: Concise overall, although the fully qualified mapping name dominates the snippet. Action granularity: Several lookup and extraction operations are combined in one expression; intermediate variables could make individual steps clearer. Reading flow: Line breaks expose the method chain, but uneven indentation and separated closing parentheses interrupt otherwise natural flow.

Run 2

Code Structure: A single, focused test is logically organized, though the assertion combines lookup, navigation, casting, and comparison. Nesting: There is no control-flow nesting, but nested calls and parentheses add visual complexity. Clarity of intent: The test name and expected value clearly convey that it checks the child ID column name. Code length: The test is concise, although the long fully qualified mapping name dominates the snippet. Action granularity: Several operations occur within one expression rather than being separated into named intermediate variables. Reading flow: The method chain is traceable, but uneven indentation, extensive line wrapping, and the inline cast interrupt natural reading.

Run 3

Code Structure: A small, focused test with a straightforward assertion. Nesting: No nested control flow, but the cast, chained calls, and assertion create substantial expression nesting. Clarity of intent: The test name and expected value clearly convey the purpose, although the long mapping name and inline column extraction obscure the actual value being checked. Code length: Concise overall, but the fully qualified class name adds visual bulk. Action granularity: Several retrieval operations and a cast are combined into one expression; a named intermediate variable would improve readability. Reading flow: The chain follows a logical order, but extensive wrapping and isolated closing parentheses interrupt scanning.