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Appian ACD201 Exam Syllabus Topics:

Topic	Details
Topic 1	Application Design and Development: This section of the exam measures the skills of Appian Developers and covers translating business requirements into user stories, building end-to-end applications, managing object security, applying design best practices, and ensuring user-centric experiences through proper UX design.
Topic 2	Advanced Appian Concepts: This section of the exam measures the skills of Solution Architects and covers creating and configuring authentication methods, setting up integration objects, designing APIs, evaluating smart services and plug-ins, and applying SSO mechanisms with SAML and LDAP.
Topic 3	Performance and Scalability: This section of the exam measures the skills of Appian Developers and covers designing performant components, building memory-efficient models, conducting database load and automated testing, analyzing server memory and logs for risks, and resolving performance concerns for end users.
Topic 4	Data Management: This section of the exam measures the skills of Solution Architects and covers designing and documenting data models, recommending record types for optimization and security, working with relational data, and implementing complex models with supporting objects.

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Appian Senior Developer Sample Questions (Q46-Q51):

NEW QUESTION # 46
You're designing a custom component rule!pagingComponent() to page through a list of items. The component must display the current page numbers being shown, as well as the total number of items. Users should be able to click arrows to increase or decrease the pagination.
Review the following:

Which two patterns should be used when calling the component in this scenario? (Choose two.)

A. A local variable local!totalCount calculated using count(local!query), which is passed into rule!pagingComponent() via a rule input. The data type of local!query is a list of record or Custom Data Type (CDT).
B. A rule input ri!pagingInfo on rule!pagingComponent() with a local variable of the same name in the main interface with an initial value. When the arrows are clicked, this updates the value of the local variable in the main interface.
C. A local variable local!pagingInfo inside rule!pagingComponent() with an initial value. When the arrows are clicked, this updates the value of the local variable.
D. Passing into the rule input totalCount of rule!pagingComponent() the value: local!query.totalCount where local!query is returning a dataSubset and returnTotalCount = "True".

Answer: B,D

Explanation:
Passing local!query.totalCount (from a dataSubset with returnTotalCount: true) into a rule input allows rule!pagingComponent() to accurately display total items for pagination.
Managing paging state (such as ri!pagingInfo) as a local variable in the main interface and updating it when arrows are clicked ensures that pagination is controlled centrally, maintaining state across the UI and allowing the component to function as intended.

NEW QUESTION # 47
You're building an application with a review workflow.
Each submission must be approved by three users who can each approve or reject their request, and leave a comment. This action changes the status of the submission to 'Approved' or 'Rejected' correspondingly, and pushes the review to the previous or next assignee.
Which data model captures the workflow requirements appropriately?

A. Two tables:
Review with columns id, statusId, comment, user
Ref Status with columns id, value
B. Two tables:
Review with columns id, statusId, comment, user1, user2, user3
Ref Status with columns id, value
C. Three tables:
Review to store id, statusId, comment
Ref Status with columns id, value
Review User with columns id, reviewId, user

Answer: C

Explanation:
Using three tables - Review, Ref Status, and Review User - enables you to track each user's approval or rejection, comments, and status changes for each review, supporting a flexible, normalized workflow for multiple reviewers.

NEW QUESTION # 48
What are three ways to optimize the memory usage of a process model? (Choose three.)

A. Divide large nodes into multiple smaller nodes.
B. Pass data directly to activity nodes and smart services.
C. Decrease the number of process variables.
D. Minimize the use of subprocesses in the model.
E. Avoid storing large blocks of text in process variables.
F. Configure process variables as parameters.

Answer: B,E,F

Explanation:
Passing data directly to activity nodes and smart services reduces unnecessary use of process variables, optimizing memory.
Configuring process variables as parameters limits their lifespan and persistence, saving memory.
Avoiding large blocks of text in process variables minimizes memory consumption within the process model.

NEW QUESTION # 49
The synced record type Customer has a one-to-many relationship with the Case record type.
You need to calculate the number of open cases for each customer.
What are two valid methods to accomplish this? (Choose two.)

A. Create a sync-time custom record field within the Customer record. Utilize the a!relatedRecordData() function to filter open cases and count the number of entries.
B. Within the Customer record type, create a custom field that evaluates in real-time to aggregate related record fields and count the open cases.
C. Within the Case record type, edit the relationship to the Customer record and select the "Open" status as the grouping filter.
D. Create a query expression for the Customer record type. Utilize the a!measure() function within the aggregation fields to count the related cases in the "Open" status.

Answer: A,B

Explanation:
A real-time custom field in the Customer record type can aggregate and count related open cases.
A sync-time custom record field using a!relatedRecordData() can filter and count open cases, making the count available as a synced field.

NEW QUESTION # 50
What are two advantages of database normalization? (Choose two.)

A. Simplifying query statements to read data.
B. Minimizing the number of tables that need to be created.
C. Minimizing data redundancy.
D. Enforcing data integrity.

Answer: C,D

Explanation:
Database normalization enforces data integrity by structuring data and relationships to prevent anomalies.
It minimizes data redundancy by ensuring each piece of information is stored only once, reducing duplication.

NEW QUESTION # 51
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