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| Section | Objectives |
|---|---|
| Topic 1: Developing in the Cloud and Best Practices | - Align software modifications with Guidewire Cloud implementation standards
|
| Topic 2: User Interface and PCF Configuration | - Configure Page Configuration Format (PCF) components and layouts
|
| Topic 3: Gosu Rules and Programming Logic | - Implement business logic and rule sets using the Gosu programming language
|
| Topic 4: Data Model and Metadata Structures | - Define and extend the application business objects schema
|
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NEW QUESTION # 108
A developer runs Database Consistency Checks for a new ClaimCenter release in a QA environment running a copy of the production database. Analysis of the output identifies data errors in both the QA and production data. Which two options follow best practices for correcting the data? (Select two)
Answer: A,C
Explanation:
Maintaining data integrity is the highest priority in a Guidewire implementation. WhenDatabase Consistency Checksidentify errors that exist in the production environment, the resolution process must be rigorous, audited, and safe.
According to theGuidewire System Health & Qualitycurriculum, developers should never attempt to fix production data errors using "ad-hoc" methods like Scratchpad (Option B) or standard Import utilities (Option C), as these bypass the complex referential integrity and validation logic inherent in the application.
Instead, the best practice involves two paths. First, for errors rooted in complex application logic, the developer shouldwrite a Gosu script and request a review from Guidewire Support(Option D). Guidewire Support provides a "Data Fix" service to ensure the script won't have unintended side effects on the database schema or application stability.
Second, if the error is purely at the database level (e.g., a broken foreign key or orphan record), the developer shouldwork with the insurer's database group to create a SQL script(Option E). However, this scriptmust be tested in a QA environment(that uses a copy of production data) before execution to verify that it correctly resolves the consistency check failure without damaging other data relationships. Option A is incorrect because "Production Data Fix Tool" is not a standard standalone tool name provided in the base product for this purpose.
NEW QUESTION # 109
Which scenarios should database consistency checks be run in? (Select two)
Answer: A,C
Explanation:
Database Consistency Checks (DCCs) are designed to verify that the data in the physical database tables aligns perfectly with the metadata definitions in the Guidewire application.
The first critical scenario is whenexternal SQL scriptsare used (Option A). Guidewire's application layer usually handles all data validation and referential integrity. When a developer or DBA runs a SQL script directly against the database, they bypass these application-level checks. Running DCCs after such an operation is mandatory to ensure that the script didn't accidentally introduce null values into non-nullable columns or break foreign key constraints.
The second scenario involvesdata imports and subtype creation(Option B). When a new subtype is created with a "required" column, and data is imported-even through the UI or staging tables-there is a risk that existing records or improperly mapped import files might result in missing data for that required field. DCCs will identify these "logical" inconsistencies where the database contains a null value for a field that the application metadata now defines as mandatory.
Options C and D involve metadata changes (UI and Typelists) that do not typically risk corrupting existing table data in a way that DCCs are designed to catch. Option E is less critical because the column is "not required," so a null value is considered consistent with the data model.
NEW QUESTION # 110
A developer is creating an entity for home inspections that contains a field for the inspection date. Which configuration of the file name and the field name fulfills the requirement and follows best practices?
Answer: E
Explanation:
Guidewire'sMetadata Naming Conventionsare strictly enforced to ensure that customer code remains distinct from Guidewire's base product code, which is essential for seamless platform upgrades.
When creating abrand-new entity, the developer must use the.eti (Entity Interface)extension. Following Cloud Delivery Standards, the entity name itself must include the_Extsuffix. Therefore, HomeInspection_Ext.
eti is the correct file structure. Regarding the fieldswithinthat custom entity, Guidewire best practices recommend applying the_Extsuffix to custom columns as well (Option B), even if the entity itself is custom.
This provides a consistent visual indicator in Gosu code that the developer is interacting with an extension rather than a base product element.
Option A and C use the .etx extension, which is reserved forextending existing base entities(e.g., adding a field to Claim). Option D is incorrect because it lacks the mandatory suffix on the entity name. Option E uses an invalid file naming format. Following the convention in Option B ensures the data model is compliant with Guidewire's automated quality gates.
NEW QUESTION # 111
An insurer plans to offer coverage for pets on homeowners policies. Whenever the covered pet Is displayed in the user interface, it should consist of the pet's name and breed. For example:
How can a developer satisfy this requirement following best practices?
Answer: C
Explanation:
InGuidewire InsuranceSuite, the global representation of a data object in the user interface is controlled by itsEntity Nameconfiguration. This configuration, stored in .en files within the metadata, defines how an instance of an entity is converted into a string whenever it is referenced in a widget like a RangeInput (dropdown), a TextCell in a list, or a read-only view.
According to theInsuranceSuite Developer Fundamentalscourse, the best practice for a requirement that applies "whenever the entity is displayed" is todefine an Entity Name(Option B). This approach allows the developer to specify a template-often involving multiple fields-that the application server uses automatically. In this scenario, the developer would configure the Pet_Ext entity name to return a string like this.Name + " - " + this.Breed.
This method is superior to other options for several reasons:
* Centralization:You define the display logic once. If the business later decides to include the pet's age or color, you only update the .en file, and the change propagates across the entire application instantly.
* Performance:The Guidewire platform caches these display names efficiently. Using logic in every PCF (Option A) or creating manual display keys (Option D) increases the maintenance burden and can lead to inconsistent UI if a developer misses a specific screen.
* Declarative Nature:It follows the Guidewire philosophy of using metadata for structural and identity- related logic, keeping Gosu code reserved for complex business processes.
Options likePost On Change(Option A) are designed for UI refreshes and cannot change the underlying string representation of an object. ASetter(Option C) is used for writing data to the database and is irrelevant to how data is formatted for viewing.
NEW QUESTION # 112
Given the following code example:
Code snippet
var query = gw.api.database.Query.make(Claim)
query.compare(Claim#ClaimNumber, Equals, "123-45-6798")
var claim = query.select().AtMostOneRow
According to best practices, which logic returns notes with the topic of denial and filters on the database?
Answer: B
Explanation:
Efficiency in Guidewire performance relies heavily on the "Database-First" principle. To fulfill the requirement of filtering notes by bothClaimandTopicspecifically on the database, a new query must be constructed using theQuery API.
Option C is the only correct answer because it uses the .compare() method to apply two specific filters:
* Topic Filter:It filters for the specific typecode TC_DENIAL.
* Claim Filter:It links the query to the specific claim object found in the previous step.
By setting these parametersbeforecalling .select(), Guidewire generates a single SQL statement: SELECT * FROM cc_note WHERE topic = 'denial' AND claimid = .... The database performs the heavy lifting and returns only the relevant records.
Options A and B areanti-patterns. They fetch all notes (Option B) or execute a broad query (Option A) and then use the Gosu .where() method to filter in the application server's memory. This is highly inefficient.
Option D is incomplete as it would returneverydenial note in the entire system, regardless of which claim it belongs to.
NEW QUESTION # 113
......
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