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We can use the then method in Rest Assured. It is mainly used to validate a Response obtained from a request. Thus, most assertions are included within a then method.SyntaxRestAssured.baseURI = "http://dummy.restapiexample.com"; //GET operation with then methods given() .when().get("/api/v1/employees").then() //verify status code as 404 .assertThat().statusCode(404);ExampleCode Implementationimport org.testng.annotations.Test; import static io.restassured.RestAssured.*; import io.restassured.RestAssured; public class NewTest { @Test void test() { //base URL RestAssured.baseURI = "http://dummy.restapiexample.com"; //input details for GET request given() .when().get("/api/v1/employee/1") ... Read More
We can create a Cucumber project template using Maven. This can be done by following the below steps −Step1− Click on the File menu in Eclipse. Then select the option New. Next click on Other.Step2− Click on Maven Project from the Maven folder. Then click on Next.Step3− Proceed with the further steps.Step4− Select maven-archetype-quickstart template. Then click on Next.Step5− Add GroupId as Automation, Artifact Id as Cucumber, and proceed.Step6− A project should get created with a Cucumber-type project structure. The Cucumber-related scripts should be written within the src/test/java folder.
We need to install the Natural plugin in Eclipse to work with Cucumber. To install it follow the below steps −Step 1 − Click on the Help menu in Eclipse, then select Eclipse MarketplaceStep2 − Enter Natural in the Find field and click on Go. Then click on Install.Step 3 − Proceed with the installation process.Step 4 − After installation is completed, click on the Restart Now button to restart Eclipse again.Step 5 − Again launch Eclipse, then click on the Help menu, then select Eclipse Marketplace. Enter Natural in the Find field and click on Go. Now, the Natural plugin shall be shown as ... Read More
Extraction is the service of extracting information from a source system for additional help in a data warehouse environment. It is the first procedure of the ETL process. After the extraction, this data can be changed and loaded into the data warehouse. The source systems for a data warehouse are usually transaction processing software. It is the source systems for a sales analysis data warehouse can be an order entry system that data all of the current order activities.Data extraction is where data is considered and moved through to fetch relevant information from data sources (such as database) in a ... Read More
An artificial neural network is a system located on the services of biological neural networks. It is a simulation of a biological neural system. The characteristic of artificial neural networks is that there are multiple architectures, which consequently needed several methods of algorithms, but despite being a complex system, a neural network is nearly simple.These networks are among the unique signal-processing technologies in the director’s toolbox. The area is highly interdisciplinary, but this method will restrict the look to the engineering outlook.In engineering, neural networks deliver two important functions as pattern classifiers and as non-linear adaptive filters. An Artificial Neural ... Read More
Operational DatabaseThe Operational Database is the source of data for the data warehouse. It contains detailed data used to run the normal operations of the business. The data generally changes as updates are created and reflect the latest value of the final transactions. It is also called OLTP (Online Transactions Processing Databases), which are used to manage dynamic data in real-time.The requirement of the operational database being simply controlled insertion and updating of information with efficient access to data manipulation and viewing mechanisms.Data WarehouseData Warehouse Systems serve users or knowledge workers for data analysis and decision-making. Such systems can construct ... Read More
Pruning is the procedure that decreases the size of decision trees. It can decrease the risk of overfitting by defining the size of the tree or eliminating areas of the tree that support little power. Pruning supports by trimming the branches that follow anomalies in the training information because of noise or outliers and supports the original tree in a method that enhances the generalization efficiency of the tree.Various methods generally use statistical measures to delete the least reliable departments, frequently resulting in quicker classification and an improvement in the capability of the tree to properly classify independent test data.There ... Read More
A decision tree is a flow-chart-like tree mechanism, where each internal node indicates a test on an attribute, each department defines an outcome of the test, and leaf nodes describe classes or class distributions. The highest node in a tree is the root node.Algorithms for learning Decision TreesAlgorithm − Create a decision tree from the given training information.Input − The training samples, samples, described by discrete-valued attributes; the set of students attributes, attribute-list.Output − A decision tree.MethodCreate a node N;If samples are all of the same class, C thenReturn N as a leaf node labeled with the class CIf the ... Read More
There are two types of statistical-based algorithms which are as follows −Regression − Regression issues deal with the evaluation of an output value located on input values. When utilized for classification, the input values are values from the database and the output values define the classes. Regression can be used to clarify classification issues, but it is used for different applications including forecasting. The elementary form of regression is simple linear regression that includes only one predictor and a prediction.Regression can be used to implement classification using two various methods which are as follows −Division − The data are divided ... Read More
There are the following pre-processing steps that can be used to the data to facilitate boost the accuracy, effectiveness, and scalability of the classification or prediction phase which are as follows −Data cleaning − This defines the pre-processing of data to eliminate or reduce noise by using smoothing methods and the operation of missing values (e.g., by restoring a missing value with the most generally appearing value for that attribute, or with the best probable value established on statistics). Although various classification algorithms have some structures for managing noisy or missing information, this step can support reducing confusion during learning.Relevance ... Read More