Pass the Salesforce Developers PDII Questions and answers with Dumpstech

Salesforce enforces a strict restriction: Actual network callouts are prohibited during unit tests. This is to ensure that tests are deterministic, fast, and do not rely on the availability or state of external third-party systems. When the testing engine encounters a System.Http.send() or a web service call without a mock, it throws the error: "Methods defined as TestMethod do no1t support Web servi2ce callouts."34

To resolve this, the developer must provide a Mock Implementation. By using Test.setMock() (Option D), the developer instructs the Apex runtime to intercept any callouts and return a pre-defined response instead of attempting a real connection. The mock class5 must implement either the HttpCalloutMock interface (for REST) or the WebServiceMock interface (for SOAP).

Furthermore, the call to the mock and the callout method should be wrapped in Test.startTest() and Test.stopTest().6

Test.startTest(): Resets governor limits, providing a fresh context for the specific logic being tested.7

Test.stopTest(): Forces any asynchronous processing (often used in cal8louts, such as @future or Queueable) to complete before the next line of code executes.

In the provided code, Test.setMock must be called before CalloutUtil.sendAccountUpdate for the platform to know which mock to use. Once Test.stopTest() is reached, the mock response is processed, the checkbox is updated, and the subsequent SOQL query and assertion will correctly see the updated data. Option A is a poor practice because it skips the logic entirely, resulting in 0% code coverage for the integration logic.

3233

When a requirement specifies a "non-linear" or highl34y customized layout, the high-35level lightning-record-form (A) is unsuitable because it automatically renders fields in a standard grid or based on a page layout. To achieve a custom UI—such as overlaying fields on a product image—the developer needs more granular control.

The lightning-record-edit-form (B) is the ideal container for this scenario. It provides the heavy lifting for data communication (loading and saving records) without imposing a strict visual structure. Within this form, the developer uses lightning-input-field (C) components for each Case field. These components are "context-aware," meaning they automatically inherit metadata like field labels, picklist values, and validation rules directly from the Salesforce object definition.

Because lightning-input-field components can be placed anywhere inside the lightning-record-edit-form tag, the developer can use custom CSS (absolute positioning or CSS Grid) to place them precisely over the product image as requested. Standard lightning-input (D) components could work but would require much more manual code to handle data binding, type conversion, and validation, making the combination of B and C the most efficient and platform-aligned approach.

==========

In Aura components, the <aura:if> tag is "lazy." It does not instantiate or render the components within its body until its isTrue expression evaluates to true. In the provided code, showContactInfo is defaulted to true. This means that when the parent component begins its initialization, it immediately starts creating and rendering the child component simultaneously.

By changing the default for showContactInfo to "false" (Option C), the developer implements a "Lazy Loading" pattern. The parent component will load quickly because it skips the heavy lifting required to render the child. The init handler then runs, retrieves the necessary data, and sets the boolean to true only when the data is ready. This improves the "perceived performance" and the Initial Page Load time.

Option A is incorrect because it increases the complexity and weight of the parent component, likely making it slower. Option B (changing to a Map) does not fundamentally affect the rendering engine's speed. Starting with the display attribute as false ensures the browser only renders what is absolutely necessary during the critical first few milliseconds of the page load.

This scenario highlights a common conflict in multi-admin environments known as "the last delivery wins" problem. When multiple administrators work in isolated sandboxes, they are essentially working on different versions of the same metadata. If Admin A adds a field to a Page Layout and deploys it, and then Admin B—who does not have Admin A's changes in their sandbox—deploys their own version of that same Page Layout, Admin B's deployment will overwrite Admin A's changes in Production (Statement B). In the Metadata API (which Change Sets use), Page Layouts are treated as single files; you cannot "merge" them via a Change Set; you can only replace the destination file entirely.

To resolve this, the team needs a more sophisticated deployment pipeline. Statement D is the correct resolution: the company should implement a "Staging" or "Integration" sandbox. In this model, all admins deploy their Change Sets to a single unified sandbox first. This allows them to identify conflicts and "merge" their changes (manually or via source control) before a final, combined deployment is made to Production. Statement A is technically incorrect because Change Sets cannot "delete" components; they can only overwrite or add. Statement C is a myth; Page Layouts can be safely deployed, but only if the underlying fields and security settings are also included and coordinated.

Jest is a powerful JavaScript testing framework used for Lightning Web Components (LWC) to ensure individual units of code function correctly in isolation. One of the primary reasons to use Jest is to verify the DOM output of a component (D). Since LWC is a UI framework, Jest allows developers to inspect the rendered HTML to ensure that elements, classes, and data are displayed as intended after a state change. Furthermore, Jest is essential for testing basic user interaction (A). Developers can simulate events like button clicks or text input and then assert that the component’s state or UI updates accordingly.

Another critical use case is to verify that events fire when expected (E). Components often communicate with parents via custom events; Jest allows you to "spy" on these events to ensure they are dispatched with the correct detail payload at the right time. Conversely, Jest is not intended for testing how multiple components work together (C)—this is the domain of integration tests or end-to-end tests (like UTAM). Additionally, Jest tests should focus on the component's public API and observable behavior; testing non-public (private) properties (B) is generally discouraged as it leads to brittle tests that break upon internal refactoring. By focusing on DOM output, interactions, and events, Jest provides a fast, reliable way to maintain component quality.

==========

In Large Data Volume (LDV) environments, Salesforce uses the Query Optimizer to determine if a query can use an index. A query is "selective" if it filters the records using an indexed field and reduces the result set to less than 10% of the first million records.

Option A is highly selective. The Id field is the primary key and is always indexed. Filtering by a list of IDs is the most efficient way to query records because it allows the database to perform a direct index lookup.

Option B is selective because it filters on the Name field (which is a standard indexed field) and Customer_Number__c. In the context of PDII, a field like "Customer Number" is typically marked as an External ID, which automatically creates a custom index. Even without the second filter, the IN clause on an indexed field like Name makes the query selective.

Option C is non-selective because negative filters (using !=) and "not null" checks generally force the database to perform a full table scan. Option D is non-selective because it uses a leading wildcard (%Partner). While the Name field is indexed, the index cannot be used if the search string starts with a wildcard, as the database must inspect the end of every string in the table.

When processing large data volumes in Apex, the "Heap Size" limit (6MB for synchronous, 12MB for asynchronous) is a common bottleneck. This limit tracks the amount of memory consumed by objects and variables currently in scope.

Option B utilizes the SOQL For Loop pattern. This is the most memory-efficient approach because it processes records in "chunks" of 200 at a time using internal query locators. Instead of loading the entire result set (potentially thousands of records) into a single collection in memory, the SOQL For Loop iterates through the records without ever holding the full set in the heap. This prevents the "Apex heap size too large" error when dealing with high-volume queries.

In contrast, Options A, C, and D all involve assigning the entire query result to a collection (a Map or List) before the loop begins. This immediately consumes heap space proportional to the number of records and fields retrieved. If the query returns a large number of records, these collections will quickly exceed the heap limit before the first line of the loop even executes. Therefore, for bulk data processing where memory efficiency is the priority, the inline SOQL For Loop (Option B) is the standard best practice.

While Salesforce highly recommends Lightning Web Components (LWC) or Aura components for modern UI development, there are specific legacy use cases where Visualforce is still the required technology. The most prominent of these is rendering a page as a PDF.

Visualforce provides the renderAs="pdf" attribute on the <apex:page> tag, which utilizes a server-side engine to convert the HTML markup into a downloadable PDF document. Neither Lightning Web Components nor Aura components have a native, built-in capability to render directly to PDF on the server side; they rely on client-side rendering or third-party libraries/services. Therefore, if the requirement is native PDF generation, Visualforce is the correct choice.

In software engineering, the DRY (Don't Repeat Yourself) principle is fundamental for maintainability. If the logic for normalizing an address is identical for both Accounts and Contacts, that logic should not be duplicated across two separate trigger files.

The optimal implementation (Option D) is to create a single Trigger Helper or Utility class. This class contains a static method (e.g., AddressService.normalize(List records)) that performs the normalization logic. You then create a small trigger on the Account object and a small trigger on the Contact object, both of which simply invoke this shared helper method.

This approach offers several advantages:

Maintainability: If the company standard for addresses changes (e.g., changing "St." to "Street"), the developer only needs to update the code in one place.

Reusability: The helper method can also be called from other contexts, such as an Anonymous Apex script or a Batch job.

Readability: Triggers remain "thin" and easy to read, acting only as entry points rather than containing complex business logic.

Options B and C are technically impossible; a trigger on one object cannot "call" a trigger on another object directly. Option A is less optimal because it leads to code duplication and a higher risk of bugs when logic is updated in one trigger but forgotten in the other.

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.