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| Section | Objectives |
|---|---|
| Topic 1: Gosu Rules and Programming Logic | - Implement business logic and rule sets using the Gosu programming language
|
| Topic 2: Data Model and Metadata Structures | - Define and extend the application business objects schema
|
| Topic 3: Developing in the Cloud and Best Practices | - Align software modifications with Guidewire Cloud implementation standards
|
| Topic 4: User Interface and PCF Configuration | - Configure Page Configuration Format (PCF) components and layouts
|
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NEW QUESTION # 44
An insurer wants to prevent US phone numbers from containing the string " 555 " in the prefix (digits 4-6). In addition to a test for country, which validation expression will accomplish this?
Answer: B
Explanation:
In Guidewire PCF Configuration, a Validation Expression is used on input widgets to enforce data quality.
These expressions must evaluate to a specific return type: if the data is valid, the expression must return null.
If the data is invalid, it must return a String (usually via a DisplayKey) containing the error message that will be displayed to the end-user.
To address the specific requirement of checking digits 4 through 6, developers use Gosu Slicing on the phone number string. Since Gosu (and most programming languages) uses 0-based indexing, the 4th digit is at index
3, the 5th at index 4, and the 6th at index 5. Therefore, the slice range is [3..5].
Option C is the correct implementation. It slices the NationalSubscriberNumber from index 3 to 5, converts it to a String, and checks if it equals ' 555 ' . If it matches (meaning the number is invalid), it returns the BadPhoneNumber DisplayKey. If it does not match, it returns null, signifying the data is valid.
Option A and D are incorrect because they return true on success, which is a common mistake; the UI engine interprets any non-null return value as an error message. Option B is incorrect because it uses .contains(), which would flag ' 555 ' appearing anywhere in the number, not just in the specific prefix positions requested by the business analyst. Mastering these expressions ensures that users receive immediate, accurate feedback while maintaining the integrity of the InsuranceSuite Data Model.
NEW QUESTION # 45
ABPersonVendor is an entity in the base application. An insurer needs to add a new person vendor type for auditors. Which configuration fulfills the requirement and follows the best practices?
Answer: A
Explanation:
In the Guidewire Data Model, representing specialized versions of existing objects is handled throughEntity Inheritance (Subtyping). In this scenario, an "Auditor" is a specific type of "Person Vendor." While they likely share the core attributes of a person vendor (name, tax ID, address), they may have specific requirements or behaviors unique to their role.
According to Guidewire best practices, when you need to create a specialized category of a base entity that requires its own distinct identity or specific additional fields, you should create aSubtype. Option B is the correct implementation: creating ABAuditor_Ext.eti and defining its supertype as ABPersonVendor. This allows the Auditor to inherit all fields, arrays, and foreign keys from the parent vendor entity while allowing the developer to add auditor-specific logic. The use of the .eti extension is correct for defining the new subtype entity, and the _Ext suffix follows the mandatory naming convention for custom extensions.
Option A (adding a column) is less flexible because it doesn't allow for the object-oriented benefits of subtyping, such as specific type-checking in Gosu. Option C (foreign key) creates a "Has-A" relationship rather than an "Is-A" relationship, which complicates the data model and UI logic. Option D is incorrect because an .etx file is used to add fields to anexistingentity, not to define a new specialized entity type.
Subtyping ensures that the "Auditor" can be used anywhere a "Person Vendor" is expected, providing clean, polymorphic behavior across the InsuranceSuite applications.
NEW QUESTION # 46
The Marketing department wants to add information for attorneys and doctors; For doctors, store the name of their medical school. For attorneys, store the name of their law school.
Which two data model extensions follow best practices to fulfill this requirement? (Select two)
Answer: C,D
Explanation:
When extending the Guidewire Data Model, developers must choose the most efficient storage mechanism based on the nature of the data and its relationship to existing entities. In this scenario, the requirement is to store a single piece of information-a school name-for two specific subtypes of person contacts: Doctors and Attorneys.
According to Guidewire best practices for Entity Extensions, if a piece of data has a one-to-one relationship with an entity and is a simple data type (like a String/Varchar), it should be added directly to the entity extension file (.etx) as a column. Options B and C follow this principle. By adding MedSchool_Ext to the ABDoctor entity and LawSchool_Ext to the ABAttorney entity, the developer ensures that the data is stored in the specific table where it is relevant. This avoids unnecessary complexity in the database schema and simplifies UI configuration, as the fields can be accessed directly from the object without traversing a foreign key or array.
Alternatives like creating separate entities for the school names (Options A, D, and F) or using an array on the base person entity (Option E) represent "over-engineering." Creating a separate entity and a foreign key is only recommended if the data needs to be normalized (e.g., if multiple people share the exact same school record and that record has its own attributes like address or accreditation). In the context of a Marketing request to simply capture a name, adding a varchar column with the mandatory _Ext suffix is the most performant and maintainable approach. It keeps the database joins to a minimum and follows the Guidewire
"KISS" (Keep It Simple, Stupid) principle for configuration.
NEW QUESTION # 47
What type of Assessment Check ensures that applications have monitoring and logging frameworks in place?
Answer: A
Explanation:
In theGuidewire Cloud Platform (GWCP)ecosystem, all customer implementations must pass through a series ofCloud Assurance Assessment Checks. These checks are designed to ensure that the configuration is not only functional but also maintainable and stable within a shared cloud infrastructure.
TheOperations Assessment Check(Option D) is specifically focused on the "health and observability" of the production application. According to theDeveloping with Guidewire Cloudtraining, this check verifies that the developer has implemented proper monitoring hooks and logging frameworks. This includes ensuring that logs are structured (to be easily parsed by tools like Datadog or Splunk), that appropriate log levels are used (avoiding "noisy" production logs), and that critical system events are captured to allow the Guidewire Cloud Operations team to proactively manage the environment.
WhilePerformancechecks (Option A) focus on latency andSecuritychecks (Option C) focus on PII protection, theOperationscheck ensures that when a failure occurs, the system provides enough telemetry for
"Day 2" support. Without these frameworks in place, an application is considered "un-managed," which poses a significant risk to the insurer's service level agreements (SLAs).
NEW QUESTION # 48
An insurer wants to determine how many activities have been generated to review a denial decision with an Account Manager. A developer has written this query:
uses gw.api.database.Query
var queryResults = Query.make(Activity).select().toCollection().where(
\ act - > act.ActivityPattern.Code == " account_denial " )
This query does not perform as well as it should. Where should the results be filtered to follow best practices?
Answer: A
Explanation:
In Guidewire InsuranceSuite, the performance of an application is heavily dependent on how efficiently it interacts with the database. The Gosu Query API is designed to allow developers to retrieve exactly the data they need by translating Gosu logic into optimized SQL statements.
The developer's current approach in the code snippet is a significant anti-pattern. By calling .select().
toCollection(), the system executes a broad SQL query that retrieves every single record from the Activity table and loads them into the application server ' s memory (the " Bundle " ). Only after these potentially thousands of records are in memory does the .where() block filter them. This causes high memory consumption, increased network latency, and unnecessary pressure on the application server's garbage collector.
According to the Gosu Queries lesson in the InsuranceSuite Developer Fundamentals course, the best practice is to filter results In the database (Option D). This is achieved by using the compare() or join() methods on the Query object before calling .select(). For example, using query.compare(Activity#ActivityPattern, Equals, myPattern) ensures that the filtering is handled by the database engine via a SQL WHERE clause.
Consequently, only the specific records that match the " account_denial " criteria are sent over the network and loaded into memory. Following this practice minimizes the data " payload, " reduces the execution time of the logic, and ensures the application remains scalable even as the volume of activities grows over time.
Adhering to database-side filtering is a core requirement for passing Quality Gates in Guidewire Cloud environments.
NEW QUESTION # 49
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