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commented
2 months ago Walkthrough
The pull request introduces several enhancements across different classes in the languagetool-core module. Key changes include the addition of a method to count non-whitespace tokens in the AnalyzedSentence class, optimizations in the Rule class to improve performance when handling anti-patterns, and the introduction of a minimum token count requirement in the AbstractTokenBasedRule class. Additionally, a new performance test method is added to the HunspellRuleTest class to evaluate the efficiency of the Hunspell rule. Minor adjustments in import statements are also included.
Changes
| Files | Change Summary |
|---|---|
languagetool-core/src/main/java/org/languagetool/AnalyzedSentence.java |
Added public int getNonWhitespaceTokenCount() method to retrieve the count of non-whitespace tokens. |
languagetool-core/src/main/java/org/languagetool/rules/Rule.java |
Optimized getSentenceWithImmunization method by storing getAntiPatterns() result in a local variable and modified iteration method for accessing anti-patterns. |
languagetool-core/src/main/java/org/languagetool/rules/patterns/AbstractTokenBasedRule.java |
Introduced private final byte minTokenCount to enforce a minimum token requirement and updated canBeIgnoredFor method to check against minTokenCount. |
languagetool-language-modules/de/src/test/java/org/languagetool/rules/spelling/hunspell/HunspellRuleTest.java |
Added public void testSeparateCorrectWordPerformance() for performance testing of the Hunspell rule, annotated with @Ignore. |
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Recent review details
**Configuration used: CodeRabbit UI** **Review profile: CHILL**Commits
Files that changed from the base of the PR and between c5f2b9b1062925ddaf12a97f82c072f0a51d2e33 and a329580f4e2bab5eef1916d19dbf70888345006e.Files selected for processing (4)
* languagetool-core/src/main/java/org/languagetool/AnalyzedSentence.java (1 hunks) * languagetool-core/src/main/java/org/languagetool/rules/Rule.java (1 hunks) * languagetool-core/src/main/java/org/languagetool/rules/patterns/AbstractTokenBasedRule.java (3 hunks) * languagetool-language-modules/de/src/test/java/org/languagetool/rules/spelling/hunspell/HunspellRuleTest.java (3 hunks)Additional comments not posted (10)
languagetool-core/src/main/java/org/languagetool/rules/patterns/AbstractTokenBasedRule.java (6)
`42-43`: **LGTM!** The new field `minTokenCount` is properly declared as `private` and `final`. Using `byte` type is a good choice for storing small integer values to optimize memory usage. --- `51-51`: **LGTM!** The initialization logic for `minTokenCount` is updated correctly to check if the first pattern token can match the start of a sentence using the `canMatchSentenceStart` method. This is a valid optimization. --- `54-56`: **LGTM!** Incrementing `minTokenCount` based on the `minOccurrence` of each pattern token is the correct approach. It ensures that `minTokenCount` reflects the minimum number of tokens required for the rule to match, which aligns with the purpose of introducing this field for optimization. --- `83-85`: **LGTM!** Setting the final value of `minTokenCount` by taking the minimum of the calculated `minTokenCount` and `Byte.MAX_VALUE` is the correct approach. It ensures that the value does not exceed the maximum value that can be stored in a `byte`, handling the edge case properly. --- `86-88`: **LGTM!** The new method `canMatchSentenceStart` is implemented correctly. It checks if a pattern token can match the start of a sentence based on the token's properties. Extracting this logic into a separate method improves code readability and reusability. --- `96-96`: **LGTM!** The update to the `canBeIgnoredFor` method to check if the number of non-whitespace tokens in the sentence is less than `minTokenCount` is a valid optimization. It allows quickly discarding sentences that do not have enough tokens to match the rule, aligning with the purpose of introducing `minTokenCount`.languagetool-core/src/main/java/org/languagetool/AnalyzedSentence.java (1)
`166-172`: **LGTM!** The addition of the `getNonWhitespaceTokenCount()` method is a great optimization. By returning the length of the existing `nonBlankTokens` array, it provides an efficient way to retrieve the count of non-whitespace tokens without creating additional allocations. This approach avoids unnecessary memory usage and improves performance. The `@ApiStatus.Internal` annotation appropriately indicates that this method is intended for internal use within the LanguageTool framework.languagetool-language-modules/de/src/test/java/org/languagetool/rules/spelling/hunspell/HunspellRuleTest.java (2)
Line range hint `23-36`: **LGTM!** The changes to the import statements are minor and do not affect the functionality of the test class. The static import of assertions is a good practice for readability. --- `243-270`: **Approve the addition of the performance test method.** The new `testSeparateCorrectWordPerformance` method is a valuable addition to the test suite. It provides insights into the efficiency of the Hunspell rule in processing a set of predefined German words. The use of `@Ignore` annotation ensures that the test is not executed during regular test runs, as it is intended for internal performance testing. The method follows a clear structure: 1. Initialize the language tool and retrieve the Hunspell rule. 2. Analyze the predefined words. 3. Measure the time taken to run a loop that checks for rule matches. 4. Print the elapsed time to the console. The test method does not introduce any functional changes to the existing code and serves as a useful benchmark for evaluating the performance of the Hunspell rule.languagetool-core/src/main/java/org/languagetool/rules/Rule.java (1)
Line range hint `193-208`: **LGTM! The changes optimize the method without altering its core functionality.** The introduction of the `antiPatterns` local variable to store the result of `getAntiPatterns()` is a good optimization. It ensures that the method is called only once, reducing redundant calls and improving performance. The change from a for-each loop to a traditional for loop using an index is also intentional, as indicated by the suppression annotation `//noinspection ForLoopReplaceableByForEach`. This change maintains consistency with the surrounding code and may have performance benefits. The core logic of replacing the `immunizedSentence` remains intact, preserving the method's functionality.
Quickly discard antipatterns if they're longer than the sentence. In spelling rules, antipatterns always have more than one token, so such a check speeds up getSentenceWithImmunization considerably.
This changes the output of
testSeparateCorrectWordPerformancefrom 12-20 seconds to 2.7 seconds on my machine.Summary by CodeRabbit
New Features
Bug Fixes
Tests