Sample
pyint-ef54db7554e2-I11
Split eligible integer literals into pairs of short-named intermediate variables
Scores
| Method | Score | Scale |
|---|---|---|
| Posnett | 0 | 0–1; higher is more readable |
| Dorn | 0.873 | 0–1; higher is more readable |
| Mi | 0.502 | 0–1; higher is more readable |
| LLOC | 41 | Logical lines; fewer is more readable |
| DeepSeek V4 Pro | 16.33 | 0–20; mean of three runs |
| GPT-6.1 Sol | 17 | 0–20; mean of three runs |
| BTTF | 0.564 | 0–1; higher is more readable |
Views
Loading feature diagnosis…
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. | 2303.37 | −76.011 |
| Source linesThe number of non-empty source lines. | 67 | +26.8 |
| Byte entropyHow varied the bytes in the source text are. Repeated bytes give a lower value; a more even mixture gives a higher value. | 4.54 | −6.809 |
Intercept 8.87 + feature contributions = -47.151 (log-odds).
Score = sigmoid(-47.151) = 0.
Feature contributions
| Feature | Value | Contribution (log-odds) |
|---|---|---|
| Indentation frequencyHow rapidly indentation changes from line to line. | 62 | +1.407 |
| Comment layout frequencyHow frequently the layout switches between lines containing only comments or whitespace and lines containing code. | 68 | −1.371 |
| Comment layout (horizontal)How rapidly the visual pattern of comment characters changes from left to right. | 87.971 | +0.615 |
| Identifier layout (vertical)How rapidly the visual pattern of identifier characters changes from top to bottom. | 66.944 | +0.526 |
| Number layout frequencyHow rapidly the number of numeric values per line changes through the code. | 1 | +0.398 |
| Operator visual areaThe share of the code’s visual area occupied by operators such as +, =, and *. | 0.061 | +0.345 |
| 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. | 87.985 | −0.061 |
Intercept 0.07 + feature contributions = 1.928 (log-odds).
Score = sigmoid(1.928) = 0.873.
| Score | 0.502 |
|---|
| Score | 41 |
|---|
Run 1
The code is well-structured with clear logical organization: imports are grouped logically, the class has a clear docstring, and methods are concise. Nesting is minimal, with only one level in the constructor and clean method. Intent is clear throughout—the field validates values against a parent instance. Code length is appropriate with no unnecessary verbosity. Action granularity is mostly one action per line, though some lines like chained getattr calls in the clean method could be considered slightly dense but remain readable. Reading flow is natural, with straightforward method ordering and intuitive variable naming. Minor deductions for the parent_instance arguments potentially hurting reusability, but overall this is Django-quality readable code.
Run 2
The code is generally readable with clear structure and logical organization. Imports are well-grouped and the class has a clear single responsibility. The constructor and methods are concise and purpose-driven. However, readability is slightly reduced by the nested conditional logic in __init__ and clean, the somewhat ambiguous to_field handling, and the multiple operations in the clean method that could be broken down further. Comments are helpful but sparse.
Run 3
The code is generally readable with clear structure and intent. The class definition is logical, and the `clean` method flows naturally. However, there are minor issues: the `__init__` method has a somewhat tangled conditional block for setting `initial`, which could be simplified or extracted. The `clean` method has a bit of branching that slightly interrupts the reading flow, especially with the inline comment breaking the sequence. Action granularity is mostly good, though the `if self.to_field` blocks repeat similar logic and could be condensed. Naming is clear, and the use of Django conventions is consistent. Overall, it is well-organized but not flawless.
Run 1
Code Structure: The class is logically organized into initialization, validation, and change detection, although many imports are unused in this snippet. Nesting: Conditional nesting is shallow, and early returns keep validation straightforward. Clarity of intent: Descriptive method and attribute names, a docstring, and comments communicate the parent-instance validation purpose; however, 'orig' is vague, and the unconditional has_changed() result lacks explanation. Code length: The implementation is concise, but the extensive import block adds unnecessary reading overhead. Action granularity: Statements generally perform one action per line, with readable formatting for longer calls. Reading flow: Initialization naturally precedes cleaning and change detection, and clean() progresses clearly from empty-value handling to comparison and return. Minor spacing and comment-quality issues slightly reduce polish.
Run 2
Code Structure: The class is logically organized into initialization, validation, and change detection, although many unused imports distract from its scope. Nesting: Branching is shallow, and early returns keep validation straightforward. Clarity of intent: The class docstring, descriptive attributes, and explicit validation error make the purpose clear; however, 'orig' is vague, the integer-field description conflicts somewhat with string comparison, and the unconditional has_changed() result lacks explanation. Code length: Methods are concise, but the import block is unnecessarily large for this snippet. Action granularity: Statements generally perform one action per line, with readable multiline formatting. Reading flow: Initialization naturally precedes validation and change detection; comments help explain behavior, though the historical comment about acting 'as we did before' provides little standalone context.
Run 3
Code Structure: The class is logically organized into initialization, validation, and change detection, although many unrelated imports clutter the snippet. Nesting: Conditional nesting is shallow and manageable, with early returns simplifying validation. Clarity of intent: Descriptive class and method names, a docstring, and comments communicate the purpose; abbreviated names such as 'orig' and framework-specific behavior require some context. Code length: The implementation is concise, but unused imports add unnecessary length. Action granularity: Each statement performs a single clear action, and multiline calls improve readability. Reading flow: Initialization naturally precedes validation and change detection. Minor weaknesses include the vague historical comment and the unexplained unconditional False in has_changed.