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| Section | Objectives |
|---|---|
| Topic 1: Integration and APIs | - Web services and integration patterns - Inbound and outbound integration mechanisms |
| Topic 2: Business Rules and Logic | - Rule execution order and lifecycle - Validation rules and workflows |
| Topic 3: Testing and Debugging | - Debugging tools and techniques - Unit testing in Guidewire environment |
| Topic 4: Data Model and Configuration | - Typelist configuration and metadata - Entity model and extensions |
| Topic 5: Gosu Programming | - Business logic implementation in Guidewire - Core Gosu syntax and constructs |
| Topic 6: User Interface (PCF) | - UI customization and navigation flows - Page Configuration Files (PCF) structure |
| Topic 7: Guidewire Platform Fundamentals | - Platform architecture basics - InsuranceSuite product overview |
| Topic 8: InsuranceSuite Architecture | - Data flow and system integration concepts - PolicyCenter, BillingCenter, ClaimCenter interaction |
| Topic 9: Deployment and Environment Management | - Deployment lifecycle and best practices - Environment configuration |
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NEW QUESTION # 97
This sample code uses array expansion with dot notation and has performance issues:
What best practice is recommended to resolve the performance issues?
Answer: B
Explanation:
In the Guidewire InsuranceSuite Developer training, specifically within the Advanced Gosu modules, the " Array Expansion Operator " (*.) is identified as a double-edged sword. While it provides a clean, declarative syntax for gathering properties from an array of objects into a new collection, it is a common source of performance degradation in complex configurations.
The technical reason for this performance hit is that every time the expansion operator is invoked, Gosu must create an intermediate, temporary collection in memory to hold the projected values. If you are expanding multiple levels (e.g., Claim.Exposures*.Contacts*.Address), the system is essentially building multiple " throwaway " lists in the application server ' s heap. For large datasets, this leads to high memory overhead and triggers frequent garbage collection cycles, which slows down the entire application.
Guidewire's official recommendation is to rewrite the code using a nested for loop (Option A). By using explicit procedural iteration, the developer eliminates the need for these hidden intermediate collections. A nested loop allows for " streaming " the data-processing each item as it is reached rather than collecting everything into a list first. This is significantly more memory-efficient. Additionally, nested loops allow developers to integrate " early exit " logic or filters that can prevent the system from even attempting to load certain records from the database, further optimizing the transaction. Following this best practice ensures that the code is not only easier to debug using the Guidewire Profiler but also scales predictably as the insurer ' s data volume grows.
NEW QUESTION # 98
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: A
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 # 99
There is a requirement for an additional filter on Desktop Activities. The filter requires a complex query.
Which option will meet the requirement and follow best practices?
Answer: A
Explanation:
In Guidewire InsuranceSuite, implementing filters on high-volume pages like Desktop Activities requires a deep understanding of performance and the Gosu Query API. When a business requirement involves a " complex query " -typically meaning logic that spans across multiple related entities or involves conditional logic that cannot be expressed in a simple ToolbarFilterOption-the best practice is to encapsulate that logic within a separate Gosu function.
Using a function that utilizes a subselect clause is a preferred architectural pattern for complex filtering. A subselect allows the database engine to perform the filtering logic entirely at the SQL level (e.g., using an EXISTS or IN clause) without pulling large amounts of data into the application server ' s memory. This is significantly more efficient than retrieving a list of objects and then filtering them in Gosu (as suggested in Option A or B). In the context of PCF Configuration, the filter property of a ToolbarFilterOption or a Filter widget can call this function, which returns a Query object.
By returning a Query instead of a list of results, the UI component can further optimize the database call with paging and sorting logic. Option B, which suggests using for loops and if statements, is a direct violation of performance standards as it would result in " N+1 " query problems and excessive memory consumption on the application tier. Therefore, leveraging the power of the Query API with subselects ensures that the application remains responsive even as the volume of activities grows.
NEW QUESTION # 100
Which scenarios should database consistency checks be run in? (Select two)
Answer: C,D
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 # 101
A developer has completed a configuration change in an InsuranceSuite application on their local environment. According to the development lifecycle described in the training, which initial steps are required to move this change towards testing and deployment? Select Two
Answer: D,E
Explanation:
TheGuidewire Cloud Platform (GWCP)development lifecycle is built around a modern CI/CD (Continuous Integration/Continuous Delivery) pipeline. This process moves code from a developer's local workstation through various "Planets" (environments) using integrated tools like Bitbucket, TeamCity, and Guidewire Home.
The first step in moving a local change toward production is committing andpushing the code to Bitbucket (Option C). Bitbucket serves as the centralized Git-based source code repository. This action triggers the
"Build" phase of the lifecycle. Once the code is in Bitbucket, the next step involves the CI server,TeamCity.
TeamCity is responsible for compiling the Gosu code, running automated GUnit tests, and performing static code analysis (Quality Gates). While TeamCity is often configured to trigger automatically upon a push, a developer may need to manuallytrigger or monitor the build via Guidewire Home(Option D) if they need immediate feedback or if the automation is set to a specific schedule.
Options such as "Deploying directly to pre-production" (Option A) are impossible in the GWCP model, as code must first pass through the "Dev" planet and satisfy quality gates before being promoted. "Scheduling automated builds" (Option B) is an administrative task, not an initial step for a developer's specific change.
Finally, "creating a star system" (Option E) refers to the infrastructure setup usually handled by Guidewire Cloud operations, not a part of the standard code-change lifecycle. Following the C and D sequence ensures that the code is properly versioned, tested, and validated before it ever reaches a runtime environment.
NEW QUESTION # 102
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