Sample
Scalabrio24
Human rating uses the original dataset scale.
Scores
| Method | Score | Scale | Dataset rank (0–100) |
|---|---|---|---|
| Posnett | 0.009 | 0–1; higher is more readable | 81.9Δ 28.9 |
| Scalabrino | 0.614 | 0–1; higher is more readable | 61.3Δ 8.3 |
| Dorn | 0.045 | 0–1; higher is more readable | 7.0Δ 46.0 |
| Mi | 0.145 | 0–1; higher is more readable | 40.7Δ 12.3 |
| LLOC | 7 | Logical lines; fewer is more readable | 81.7Δ 28.6 |
| DeepSeek V4 Pro | 15.67 | 0–20; mean of three runs | 72.9Δ 19.8 |
| GPT-6.1 Sol | 18 | 0–20; mean of three runs | 83.7Δ 30.7 |
| BTTF | 0.388 | 0–1; higher is more readable | 12.6Δ 40.5 |
| Human | 3.67 | 1–5; original rating | 53.0 |
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Source regions
Feature contributions
Feature contributions
| Feature | Value | Contribution (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. | 322.023 | −10.627 |
| Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value. | 4.867 | −7.301 |
| Source linesThe number of non-empty source lines. | 11 | +4.4 |
Intercept 8.87 + feature contributions = -4.658 (log-odds).
Score = sigmoid(-4.658) = 0.009.
| Score | 0.614 |
|---|
Feature contributions
| Feature | Value | Contribution (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. | 155 | −2.9 |
| Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right. | 0 | −0.804 |
| Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code. | 11 | +0.647 |
| Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *. | 0.049 | +0.467 |
| Indentation frequencyHow rapidly indentation changes from line to line. | 9 | −0.426 |
| Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom. | 9.763 | −0.273 |
| Number layout frequencyHow rapidly the number of numeric values per line changes through the code. | 11 | +0.168 |
Intercept 0.07 + feature contributions = -3.051 (log-odds).
Score = sigmoid(-3.051) = 0.045.
| Score | 0.145 |
|---|
| Score | 7 |
|---|
Run 1
The code is well-structured and readable. It clearly separates test setup, expected value construction, actual method call, and assertion. Nesting is flat, with no conditional complexity. Intent is explicit: testing limit/offset insertion with FOR UPDATE and WITH clauses. Variable naming is descriptive. The expected string concatenation is the only minor readability issue, as it breaks natural reading flow slightly, but it remains clear. The test method name is appropriately verbose for clarity. Overall, concise and maintainable.
Run 2
The code is reasonably structured and readable for a test method. It clearly separates test data setup (limit, offset, input, expected) from the actual action and assertion. Nesting is minimal, and each line expresses a single clear action. However, readability is hindered by long string literals containing SQL, especially the concatenated expected string which wraps awkwardly across lines and mixes string concatenation with inline SQL syntax. The variable names are clear, and the intent is unambiguous, but the visual noise of the long SQL strings reduces overall clarity. The test method name is descriptive, and the reading flow is natural. Overall, it follows good test structure, but could benefit from formatting improvements or constants for SQL fragments to reduce clutter.
Run 3
The code is readable and well-structured for a test method. It clearly separates input, expected, and actual values, with descriptive variable names. The method name indicates intent well. However, readability is slightly reduced by the long SQL strings that require horizontal scrolling and the multi-line concatenation in the expected string, which interrupts the reading flow. The instantiation of LocalDerbyDialect inline in the method call is acceptable but could be extracted for clarity. Overall, the code is straightforward, flat, and follows good unit testing conventions, but the verbosity of SQL strings and concatenation impacts its overall readability score.
Run 1
Code Structure: The test is logically organized into setup, execution, and assertion. Nesting: There is no nested control flow, making it easy to scan. Clarity of intent: The descriptive method name and input, expected, and actual variables clearly communicate the behavior being tested. Code length: The test is concise, though long SQL literals require horizontal scanning. Action granularity: Each statement performs one clear action; the multiline concatenation only constructs the expected string. Reading flow: The arrangement follows a natural testing sequence, with minor readability friction from the lengthy SQL and wrapped string concatenation.
Run 2
Code Structure: The test is logically organized into setup, execution, and assertion. Nesting: There is no nested control flow. Clarity of intent: The descriptive method name and input, expected, and actual variables clearly communicate the behavior under test. Code length: The test is concise, though long SQL literals make individual lines harder to scan. Action granularity: Each statement performs one clear action; the wrapped concatenation remains a single coherent expression. Reading flow: The progression is natural and easy to follow, with minor readability costs from horizontal line length and string concatenation.
Run 3
Code Structure: The test is logically organized into setup, execution, and assertion. Nesting: The method is flat, with no nested control flow. Clarity of intent: The descriptive method name and input, expected, and actual variables clearly communicate the SQL pagination behavior being tested. Code length: The test is concise, although the long SQL literals require careful scanning. Action granularity: Each statement performs one clear action; the wrapped concatenation remains a single logical statement. Reading flow: The natural arrange-act-assert progression is easy to follow. Minor readability drawbacks include lengthy SQL lines and the visually dense expected-string construction.