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| Section | Objectives |
|---|---|
| Testing and Debugging | - Unit testing in Guidewire environment - Debugging tools and techniques |
| User Interface (PCF) | - Page Configuration Files (PCF) structure - UI customization and navigation flows |
| Business Rules and Logic | - Rule execution order and lifecycle - Validation rules and workflows |
| Gosu Programming | - Core Gosu syntax and constructs - Business logic implementation in Guidewire |
| Guidewire Platform Fundamentals | - InsuranceSuite product overview - Platform architecture basics |
| InsuranceSuite Architecture | - Data flow and system integration concepts - PolicyCenter, BillingCenter, ClaimCenter interaction |
| Deployment and Environment Management | - Environment configuration - Deployment lifecycle and best practices |
| Integration and APIs | - Inbound and outbound integration mechanisms - Web services and integration patterns |
| Data Model and Configuration | - Typelist configuration and metadata - Entity model and extensions |
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NEW QUESTION # 13
Which of the following are true about Guidewire Inspections?
Answer: B
Explanation:
Guidewire Inspections are a form of static code analysis integrated directly into Guidewire Studio (which is built on the IntelliJ IDEA platform). These inspections are designed to help developers identify code smells, performance bottlenecks, and violations of Gosu Coding Standards in real-time.
The most important operational fact about inspections (Option E) is that they run automatically as a background task within the Gosu editor. As a developer types code, the IDE continuously analyzes the syntax and logic. If a violation is found-such as an unused variable, a potentially null reference, or an inefficient query-the editor provides immediate visual feedback through highlights (like yellow warnings or red errors) and " gutter " icons. This allows for " Shift-Left " quality management, where issues are corrected the moment they are created, rather than during a later build or code review phase.
While Option C is technically true (profiles can be customized), Option E is the primary characteristic of the tool's behavior as described in the System Health and Quality training. Option B is false because Guidewire provides hundreds of out-of-the-box inspections specifically tailored for InsuranceSuite (e.g., checking for PII in logs or inefficient bundle usage). Option D is incorrect as the primary mode of interaction is the IDE, not a command-line tool. By leveraging these automatic background inspections, developers maintain a high level of code quality and adhere to the SurePath methodology throughout the development lifecycle.
NEW QUESTION # 14
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: A,E
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 # 15
In TrainingApp. the Person Info card of the Details screen for a contact has a section where basic employment information is stored:
The insurer requires this information to be displayed, in this format, on every card of both the Summary and Details screens, for every individual person contact. This information will be stored in a container to be reused on all these cards.
Which object will most efficiently meet this requirement, according to best practices?
Answer: A
Explanation:
In Guidewire InsuranceSuite development, the Page Configuration Framework (PCF) is designed around the principles of modularity and reusability. When a business requirement specifies that a group of fields-such as basic employment information-must appear identically across multiple screens (e.g., Summary and Details), the most efficient approach is to create a reusable component. According to the InsuranceSuite Developer Fundamentals course, the Input Set PCF file (Option C) is the standard object for achieving this.
An Input Set PCF file is a standalone metadata file that contains a collection of input widgets (like TextInput, DateInput, etc.). By defining the employment fields in a single Input Set file, you create a " source of truth. " To display these fields on different screens, a developer simply adds an InputSetRef widget to the target Detail View or Page and points it to the employment Input Set file. This architectural pattern ensures that if the business later decides to add a " Work Phone " or " Employee ID " field, the developer only needs to update one file. This update then automatically reflects across all screens where the Input Set is referenced, significantly reducing maintenance effort and the risk of UI inconsistency.
Other options are less suitable for this specific task. A Detail View Panel (Option A) is a higher-level container; while it can be reused, it is generally intended to hold larger sections of a page and may contain logic that isn ' t applicable to every card. An Input set widget (Option B) is merely a structural element within a single PCF file and does not provide cross-file reusability on its own. A Worksheet (Option D) is a UI element that slides up from the bottom of the application window and is not intended to be embedded directly into the layout of a Summary or Details card. Therefore, the Input Set PCF file is the most granular and effective tool for field-level reuse.
NEW QUESTION # 16
Succeed Insurance would like a list of all Notes related to all Policies for an Account. Which approach follows best practices for retrieving this data more efficiently?
Answer: B
Explanation:
In Guidewire InsuranceSuite, developers frequently need to " reach across " one-to-many relationships to collect data from nested arrays. In this scenario, the goal is to retrieve a flattened list of all Note entities associated with all Policy objects linked to a specific Account.
According to Advanced Gosu best practices, the most efficient and idiomatic way to handle this is by using the Expansion Operator (*). As shown in Option B, the syntax account.Policies*.Notes performs what is known as " collection flattening. " When the expansion operator is applied to the Policies array, Gosu understands that it should look at every policy in that collection and access the Notes array for each. It then automatically flattens these multiple sub-collections into a single, comprehensive list of Note objects. Calling .
toList() at the end ensures the result is captured in a standard, manipulatable collection format.
This approach is vastly superior to nested for loops (Option C). Manual iteration through nested arrays is a primary cause of the " N+1 " query problem and " Bundle Bloat. " In nested loops, the system may perform a separate database fetch for every policy and then another for every note, loading every single entity into the current transaction bundle, which consumes excessive memory and CPU time. The expansion operator, however, is highly optimized within the Gosu Runtime to handle these traversals more gracefully.
Option D is incorrect because it uses a second expansion operator to retrieve the DisplayName property, resulting in a list of Strings rather than a list of Note entities. Option A, while using the Query API, is logically disconnected from the root account object already in memory and represents a more complex search- based approach rather than a relationship-based retrieval. Therefore, the expansion operator is the verified standard for efficient, readable data collection in Gosu.
NEW QUESTION # 17
A developer performed Guidewire Profiler analysis on a web service. The results showed a large Own Time (unaccounted-for time) value, but it is difficult to correlate the data with the exact section of code executed.
Which approach can help to identify what is causing the large processing time?
Answer: C
Explanation:
When using the Guidewire Profiler, " Own Time " refers to time spent within a specific block of code that isn
' t attributed to sub-calls (like database queries or other profiled methods). A high Own Time in a web service indicates that significant processing is happening in a " blind spot " of the current profile.
To gain visibility into these blind spots, Guidewire recommends creating custom Profiler Tags. By wrapping specific segments of your Gosu code with Profiler.push( " TagName " ) and Profiler.pop(), you manually tell the Profiler to track that specific block as its own entry in the results tree. This breaks down the generic " Own Time " into specific, labeled sections, allowing you to pinpoint exactly which loop or calculation is causing the bottleneck.
Option D is a common distractor; while " stack frames " provide context, they don ' t help categorize logic that isn ' t currently being caught by the instrumented hooks. Options B and C are manual troubleshooting methods that are significantly less efficient than using the built-in diagnostic capabilities of the Profiler and can even skew performance results due to the overhead of I/O operations.
NEW QUESTION # 18
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