Pass the Salesforce Developers PDII Questions and answers with CertsForce

In a multi-user environment, a "Race Condition" occurs when two users query the same record at the same time, see that Is_Registered__c is false, and both proceed to update it. To prevent this, developers must implement Row-Level Locking.

In Salesforce SOQL, the FOR UPDATE (Option C) keyword is used for this exact purpose. When a query includes FOR UPDATE, the platform places an exclusive lock on the records returned. If a second transaction attempts to query the same records using FOR UPDATE, it will be forced to wait until the first transaction is completed (either committed or rolled back). If the lock isn't released within 10 seconds, the second transaction throws a QueryException.

By using FOR UPDATE, the first user who executes the query "reserves" the Account. The second user's request will wait, and by the time their query actually executes and retrieves the data, Is_Registered__c will have been updated to true by the first user, thus failing the if (!account.Is_Registered__c) check and preventing a duplicate registration. Option D is a manual "optimistic locking" approach that is less reliable than the platform's native locking mechanism. Options A and B do not address the timing issue of the initial check.

To create a responsive design in Salesforce Aura components, the lightning:layout and lightning:layoutItem components utilize a 12-column grid system based on the Salesforce Lightning Design System (SLDS). The issue in the original code is that size="6" is hardcoded, which forces each item to occupy 50% of the container width regardless of the screen size. On small mobile screens, 50% width is often insufficient for text content, leading to horizontal scrolling or overlapping.

Option B resolves this by using device-specific size attributes. By setting smallDeviceSize="12", each item is instructed to take up the full width (12 out of 12 columns) on mobile devices. This causes the items to stack vertically instead of sitting side-by-side. The mediumDeviceSize="6" and largeDeviceSize="6" attributes ensure that on tablets and desktop screens, the items return to a side-by-side layout (50% width each).

For this stacking to occur, the parent lightning:layout must have the multipleRows="true" attribute enabled. This allows the layout to wrap items to a new line once the total column count in a single row exceeds 12. Without multipleRows="true", the items would try to squeeze into a single line regardless of their individual size settings, which would not solve the horizontal scrolling problem. Option B is the only choice that correctly applies the grid logic to handle multiple breakpoints effectively.

When an external application needs to request data from Salesforce, you must expose an endpoint. Since the requirement specifically mentions JSON format and a native mobile app (iOS), an Apex REST web service (Option D) is the optimal choice. REST (Representational State Transfer) is the industry-standard architecture for mobile-to-cloud integrations because it is lightweight, uses standard HTTP methods, and natively supports JSON.

By using the @RestResource and @HttpGet annotations in an Apex class, a developer can create a custom endpoint that performs complex logic, such as querying multiple objects (Accounts, Orders, Line Items), and returns a single, consolidated JSON response. This is far more efficient than the standard REST API if the mobile app would otherwise need to make multiple sequential calls to gather the same information.

Options B and C are incorrect because "callouts" are used when Salesforce requests data from an external system, not the other way around. Option A (SOAP) is a heavier, XML-based protocol that is less efficient for mobile development and does not use the JSON format natively. Therefore, a custom Apex REST service provides the best performance and flexibility for mobile integrations.

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When a Salesforce organization uses the Translation Workbench, picklist values can be translated into multiple languages. By default, a SOQL query returns the "Master" or API value of a picklist field, which is usually in English. If a developer needs the returned data to reflect the translated labels based on the current user's language settings, they must use the toLabel() function within the SOQL SELECT statement.

Using SELECT toLabel(Products__c) FROM Account (Option A) tells the Salesforce query engine to look up the translated value for each picklist entry in the result set before returning it to Apex. This is particularly useful for UI components or reports where the user expects to see values in their native tongue. It works for both standard picklists and multi-select picklists.

Other options are incorrect because they do not exist as standard Apex features. There is no translate() method on SObject records (Option B), and Apex does not allow you to manually "set the locale" on individual records to trigger translation (Option C). There is also no "locale clause" in SOQL syntax (Option D). Using toLabel() is the platform-standard, most efficient way to handle localized data retrieval directly within the data access layer.

In the Aura Component Framework, an infinite loop involving an application event is frequently caused by firing the event from a custom renderer (Option B), specifically from the afterRender or rerender functions.

The framework's rendering lifecycle is sensitive. When a component's state changes, the renderer is invoked to update the DOM. If a developer places code inside a renderer that fires an application event, and that event—or a handler of that event—subsequently modifies an attribute on the same component, the component is marked as "dirty." This triggers the renderer to run again, which fires the event again, creating an infinite loop.

Option A is incorrect because multiple handlers simply result in multiple independent blocks of code executing, not a loop. Option C relates to touch events on mobile but wouldn't cause a loop unless the handler itself re-triggered the event. Option D is incorrect because triggers are server-side and do not directly re-fire client-side application events in a looping fashion. To avoid this, event firing should be restricted to controller or helper actions that are triggered by specific user interactions or discrete system states, rather than the automatic rendering cycle.

The most fundamental best practice for writing bulk-safe (scalable) Apex triggers is to avoid performing DML operations or SOQL queries inside of loops. Salesforce enforces a limit of 150 DML statements per transaction. If a trigger iterates through a list of 200 records and performs a delete or update inside that loop, the code will fail with a governor limit exception after the 150th record.

To make a trigger bulk-safe, developers must collect all records that need to be processed into a collection (such as a List or Map) and then perform a single DML operation on that entire collection outside of the loop (Option B). This consumes only one DML statement regardless of the number of records (up to the 10,000 row limit).

Option A is incorrect because LIMIT 50000 does not help with bulk safety; it just prevents a query from exceeding the SOQL row limit. Option C (using allOrNone=false) allows for partial success of a DML operation but does not inherently make a trigger bulk-safe if the calls are still made inside a loop. Option D is incorrect because moving DML to a future method is a way to handle callouts or long-running processes, but it is not a general requirement for trigger bulkification and can lead to reaching asynchronous limits if used incorrectly.

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This scenario presents two distinct requirements: processing a large volume of data (50,000 records) and running the process at a specific time (once a day after business hours).

Database.Batchable (Option B): Processing 50,000 records in a single synchronous transaction will exceed Apex Governor Limits (specifically the CPU time limit or the heap size limit). Batch Apex allows the system to process these records in smaller chunks (batches), ensuring that the calculation completes without hitting limits.

Schedulable (Option C): To ensure the job runs "once a day after business hours," the Schedulable interface is required. The developer allows the class to be scheduled via the Apex Scheduler or the UI.

The standard pattern for this use case is to create a class that implements Schedulable, and inside its execute method, instantiate and execute the Batch class (Database.executeBatch). This combines precise timing with bulk processing capabilities.

In a private sharing model, access is restricted to the owner and those above them in the hierarchy. When a specific user is identified in a lookup field (like Event_Reviewer__c), standard sharing rules cannot dynamically grant access to that specific individual because sharing rules only target Roles, Public Groups, or Territories.1

The solution is Apex Managed Sharing (Option A). By using an after insert (and likely after update) trigger, the developer can pro2grammatically create records in the object's "Share" table (e.g., Convention_Attendee__Share). Each share record specifies the UserOrGroupId (from the lookup field), the AccessLevel ('Edit' for Read/Write), and a RowCause (Apex Sharing Reason).

The "After" trigger is required because the ID of the Convention_Attendee__c record must exist before a Share record can be associated with it. "Before" triggers (Option B) are used for field updates on the record itself, not for creating related sharing records. Options C and D are not viable because they cannot dynamically reference a User ID stored within a field on the record itself. Apex Managed Sharing provides the most granular and automated way to handle this dynamic security requirement.