UiPath Updated UiPath-ADPv1 Exam Questions and Answers by jemima

AI Computer Vision is a feature of UiPath that enables the automation of remote applications or desktops, such as Citrix Virtual Apps, Windows Remote Desktop, or VMware Horizon, by using native selectors. Native selectors are expressions that identify UI elements reliably and accurately, without relying on OCR or image recognition activities1. AI Computer Vision uses a mix of AI, OCR, text fuzzy-matching, and an anchoring system to visually locate elements on the screen and interact with them via UiPath Robots, simulating human interaction2. AI Computer Vision is especially useful for scenarios where the UI elements have low quality or scaling issues, which make them difficult to recognize with traditional methods3.

Option A is an accurate example of using AI Computer Vision features in a UiPath project, because it involves identifying and interacting with UI elements in a remote desktop application, which is one of the main use cases of AI Computer Vision. By using the Computer Vision activities, such as CV Screen Scope, CV Click, CV Get Text, etc., you can automate tasks in a remote desktop application without using selectors, OCR, or image recognition activities4.

The other options are not accurate examples of using AI Computer Vision features in a UiPath project, because they involve tasks that are not related to the automation of remote applications or desktops, or that do not use the Computer Vision activities. For example:

Option B involves training a custom machine learning model, which is not a feature of AI Computer Vision, but of the UiPath AI Fabric, a platform that enables you to deploy, consume, and improve machine learning models in UiPath.

Option C involves extracting plain text from a scanned PDF document, which is not a feature of AI Computer Vision, but of the UiPath Document Understanding, a framework that enables you to classify, extract, and validate data from various types of documents.

Option D involves performing sentiment analysis on a text string, which is not a feature of AI Computer Vision, but of the UiPath Text Analysis, a set of activities that enable you to analyze the sentiment, key phrases, and language of a text using pre-trained machine learning models.

Comprehensive and Detailed Explanation: Remote Debugging is a feature of UiPath Studio that allows developers to run and debug automation projects on robots deployed to remote machines, including on Linux robots that can run cross-platform projects1. It enables developers to connect to the remote robot using either a remote machine connection or an unattended robot connection, and then use the Studio debugging tools to inspect the execution and troubleshoot any issues1. Remote Debugging uses a web-based interface that shows the UI elements and the data of the remote machine, as well as the breakpoints, variables, and output of the project2.

The other options are incorrect because:

Option A is incorrect because Remote Debugging is not limited by the involvement of Orchestrator queues and assets in the automation project. Remote Debugging can work with any project that can be executed by a robot on a remote machine, regardless of the Orchestrator entities used1.

Option B is incorrect because Remote Debugging does not enable developers to design new UI elements for the automation project. Remote Debugging is only used for testing and debugging existing projects, not for creating or modifying them1.

Option C is incorrect because Remote Debugging does not refer to the process of testing and debugging an automation project on the same machine where UiPath Studio is installed. That process is called Local Debugging, which is the default debugging mode in Studio3.

A mock file is a copy of a workflow file that is used for testing purposes, where some activities are replaced by mock activities that simulate the expected behavior1. A mock file can be created by selecting Mock workflow under test in the Create Test Case window2. The mock file is stored in the Project > Mocks folder, and it has the same name as the original workflow file, with the suffix “_mock” added2. For example, if the original workflow file is named “MySequence.xaml”, the mock file will be named “MySequence_mock.xaml”.

When a mock file is created, the changes made in the original workflow file are automatically applied to the mock file when the project is saved2. This means that any new activities or modifications in theoriginal workflow file are reflected in the mock file, except for the activities that are surrounded by mock activities2. The mock activities are not affected by the changes in the original workflow file, and they can only be edited within the mock file2.

Therefore, if you update “MySequence” and add a Log Message activity and a Verify Expression activity, and then save the project, the changes will be applied to the mock file, assuming that the file is closed. This means that the mock file will also have the Log Message activity and the Verify Expression activity added, unless they are inside a mock activity