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Apex

Apex static code analysis

Unique rules to find Bugs, Vulnerabilities, Security Hotspots, and Code Smells in your APEX code

  • All rules 97
  • Vulnerability2
  • Bug26
  • Security Hotspot3
  • Code Smell66
Filtered: 22 rules found
salesforce
    Impact
      Clean code attribute
        1. SOQL queries should not contain hardcoded date literals

           Code Smell
        2. Apex classes should contain at most one "@InvocableMethod" annotation

           Bug
        3. SOQL queries should not be executed inside loops

           Code Smell
        4. SOSL queries in test methods should use "Test.setFixedSearchResults"

           Code Smell
        5. DML operations in catch blocks can mask original exceptions

           Bug
        6. Test classes and methods should not use "seeAllData=true"

           Code Smell
        7. HTTP requests should have explicit timeout configuration

           Code Smell
        8. Methods with "@AuraEnabled" should be public or global

           Bug
        9. Classes implementing "Database.Batchable" should be declared as "global"

           Bug
        10. "getRoleAndSubordinates()" should be replaced with "getRoleAndSubordinatesInternal()"

           Code Smell
        11. Future methods making HTTP callouts should include "callout=true" parameter

           Bug
        12. SOQL queries should use SystemModStamp instead of LastModifiedDate for better performance

           Code Smell
        13. Future methods should not call other future methods

           Bug
        14. Test classes should be annotated with "@isTest"

           Code Smell
        15. SOQL queries should include LIMIT clauses to prevent hitting governor limits

           Bug
        16. Private members made public for testing should use "@TestVisible" annotation

           Code Smell
        17. Batch Apex scope parameters should not exceed 2000 records

           Code Smell
        18. Custom event names should not be prefixed with "on"

           Code Smell
        19. Apex REST services should implement comprehensive exception handling

           Vulnerability
        20. SOQL queries should be assigned to Lists to avoid QueryException

           Bug
        21. InvocableMethod annotations should include descriptive label and description

           Code Smell
        22. URLs should not be hardcoded in Apex code

           Bug

        SOQL queries should not be executed inside loops

        intentionality - efficient
        reliability
        maintainability
        Code Smell
        • performance
        • salesforce
        • governor-limits

        This rule raises an issue when a SOQL query is executed inside a loop (for, while, or do-while), which can lead to governor limit violations and poor performance.

        Why is this an issue?

        How can I fix it?

        More Info

        Executing SOQL queries inside loops is a critical performance anti-pattern in Apex development that can quickly exhaust Salesforce’s governor limits.

        Salesforce enforces strict limits on the number of SOQL queries that can be executed in a single transaction: 100 queries in synchronous contexts and 200 in asynchronous contexts. When you place a SOQL query inside a loop, each iteration executes a separate query against the database.

        For example, if you have a loop that processes 50 records and each iteration executes one SOQL query, you’ll consume 50 of your 100 available queries in a single operation. This approach doesn’t scale - processing 150 records would exceed the governor limit and cause a runtime exception.

        Beyond governor limits, this pattern creates significant performance issues. Each SOQL query requires a round trip to the database, and multiple individual queries are much slower than a single bulk query that retrieves all needed data at once.

        The solution is to use bulk processing patterns: collect all the criteria (like IDs) before the loop, execute a single SOQL query with an IN clause or similar bulk operator, and then process the retrieved records. This approach scales efficiently regardless of data volume and respects Salesforce’s platform constraints.

        What is the potential impact?

        This issue can cause runtime exceptions when governor limits are exceeded, leading to transaction failures and poor user experience. It also creates significant performance degradation, especially as data volume increases, making applications slow and unresponsive.

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