Functional acceptance criteria are the conditions that a user story must satisfy to be accepted by the user or stakeholder. They should be specific, measurable, achievable, relevant, and testable. In this case, two functional acceptance criteria that would be considered ‘good’ are:

The user will receive an email notification when their order is completed. This is a specific, measurable, achievable, relevant, and testable criterion that describes a feature that the user needs to be informed of their order status.

The user cannot submit the form without filling out all required fields. This is a specific, measurable, achievable, relevant, and testable criterion that describes a feature that the user needs to provide valid and complete information for their order.

The other options are not as good. Option A, the user will click Save, and the order information will be saved in the ORDER table and have audit history, is not a functional acceptance criterion, but rather a technical implementation detail that is not relevant or visible to the user. Option C, the system must handle up to 500 unique orders per day, is not a functional acceptance criterion, but rather a non-functional requirement that describes a performance or quality attribute of the system.

To meet the application requirement of allowing users to navigate throughout the application while maintaining complete visibility in the application structure, and easily navigate to previous locations, you should include a breadcrumbs pattern on applicable interfaces to show the organizational hierarchy. A breadcrumbs pattern is a user interface component that displays the current location of the user within the application, and provides links to the previous levels of the hierarchy. For example, if the user is viewing a product details page, the breadcrumbs pattern could show something like “Home > Products > Product Details”. This way, the user can see where they are in the application, and easily go back to any previous level by clicking on the corresponding link.

The other options are not as effective. Option A, using Tiles as Cards pattern on the home page to prominently display application choices, would provide a way for users to access different parts of the application from the home page, but it would not show the organizational hierarchy or allow users to navigate to previous locations. Option B, implementing an Activity History pattern to track an organization’s activity measures, would provide a way for users to see the recent actions performed by themselves or others in the application, but it would not show the organizational hierarchy or allow users to navigate to previous locations. Option C, implementing a drilldown report pattern to show detailed information about report data, would provide a way for users to explore different levels of data in a report, but it would not show the organizational hierarchy or allow users to navigate to previous locations.

The option B involves the lowest additional server cost and the least code retrofit effort, as it only requires one additional environment (DEV2) for the production support work stream. The production support work stream can use the existing STAGE environment for testing and user acceptance testing, as it is shared with the phase 2 development work stream. This way, there is no need to create a separate TEST2 environment or to retrofit any code from TEST to STAGE or from STAGE to PROD. Verified References: [Appian Certified Lead Developer study guide], page 16, section “Environment Strategy”.

The field would benefit greatly from the index in the following scenarios:

A. The field contains a textual short Business code. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A textual short Business code is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.

C. The field contains many datetimes, covering a large range. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A datetime field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.

D. The field contains big integers, above and below 0. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A big integer field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.

The other options are incorrect for the following reasons:

B. The field contains long unstructured text such as a hash. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A long unstructured text field is likely to have low cardinality, meaning that it has few distinct values and high duplication. This makes the index less selective and efficient, as it cannot quickly narrow down the results based on the search criteria. Moreover, indexing a long unstructured text field could increase the storage space and maintenance cost for the database, which could affect the overall performance.

E. The field contains a structured JSON. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A structured JSON field is not a native data type in MySQL, and it requires special functions or operators to access or manipulate its elements. Indexing a structured JSON field could increase the complexity and overhead for the database, which could affect the overall performance. Verified References:  Appian Documentation , section “Query Optimization”.

To design a complex Appian integration to call a RESTful API, you need to have some prerequisites, such as:

Define the HTTP method that the integration will use. The HTTP method is the action that the integration will perform on the API, such as GET, POST, PUT, PATCH, or DELETE. The HTTP method determines how the data will be sent and received by the API, and what kind of response will be expected.

Understand the content of the expected body, including each field type and their limits. The body is the data that the integration will send to the API, or receive from the API, depending on the HTTP method. The body can be in different formats, such as JSON, XML, or form data. You need to understand how to structure the body according to the API specification, and what kind of data types and values are allowed for each field.

Understand the different error codes managed by the API and the process of error handling in Appian. The error codes are the status codes that indicate whether the API request was successful or not, and what kind of problem occurred if not. The error codes can range from 200 (OK) to 500 (Internal Server Error), and each code has a different meaning and implication. You need to understand how to handle different error codes in Appian, and how to display meaningful messages to the user or log them for debugging purposes.

The other two options are not prerequisites for designing the integration, but rather considerations for implementing it.

Understand whether this integration will be used in an interface or in a process model. This is not a prerequisite, but rather a decision that you need to make based on your application requirements and design. You can use an integration either in an interface or in a process model, depending on where you need to call the API and how you want to handle the response. For example, if you need to update a case in real-time based on user input, you may want to use an integration in an interface. If you need to update a case periodically based on a schedule or an event, you may want to use an integration in a process model.

Understand the business rules to be applied to ensure the business logic of the data. This is not a prerequisite, but rather a part of your application logic that you need to implement after designing the integration. You need to apply business rules to validate, transform, or enrich the data that you send or receive from the API, according to your business requirements and logic. For example, you may need to check if the case status is valid before updating it in the legacy system, or you may need to add some additional information to the case data before displaying it in Appian.

The correct syntax for referring to the username parameter in the Web API URL is httpirequest.queryParameters.username. This syntax allows you to access the value of the username parameter that is passed in the query string of the URL after the question mark (?). For example, if the URL is https://exampleappiancloud.com/suite/webapi/user_management/users?username=john.smith, then httpirequest.queryParameters.username will return john.smith. Verified References:  Appian Documentation , section “Web API”.

The best way to divide the work between the teams, avoiding issues caused by cross-dependency, is to group epics and stories by feature, and allocate work between each team by feature. This way, each team can focus on a specific feature and minimize the need for coordination or integration with the other team. This also reduces the risk of conflicts or errors when merging the code from both teams. Verified References:  Appian Documentation , section “Agile Development”.