Let us see one sample example of a banking application, as we can see in the below image of amount transfer. Here positive testing implies that if the total balance is Rs15, and we are transferring Rs and checking if the amount transfer works fine. If it does, then the test would be a pass. And negative testing means, if the total balance is Rs15, and we are transferring Rs20, and check if amount transfer occurs or not, if it does not occur, the test is a pass.
If it happens, then there is a bug in the code, and we will send it to the development team for fixing that bug. Let us assume that we have a Gmail application where we perform the integration testing. First, we will do functional testing on the login page , which includes the various components such as username, password, submit, and cancel button.
Then only we can perform integration testing. Secanrios2: We also perform the integration testing on Spam folders. If the particular contact has been marked as spam, then any mail sent by that user should go to the spam folder and not in the inbox.
As we can see in the below image, we will perform the functional testing for all the text fields and every feature. Then we will perform integration testing for the related functions.
We first test the add user, list of users, delete user, edit user, and then search user. Although all modules of software application already tested in unit testing, errors still exist due to the following reasons:. Any testing technique Blackbox, Whitebox, and Greybox can be used for Integration Testing; some are listed below:.
In the Incremental Approach, modules are added in ascending order one by one or according to need. The selected modules must be logically related. Generally, two or more than two modules are added and tested to determine the correctness of functions. The process continues until the successful testing of all the modules.
In this type of testing, there is a strong relationship between the dependent modules. Suppose we take two or more modules and verify that the data flow between them is working fine. If it is, then add more modules and test again. For example: Suppose we have a Flipkart application, we will perform incremental integration testing, and the flow of the application would like this:.
The top-down testing strategy deals with the process in which higher level modules are tested with lower level modules until the successful completion of testing of all the modules. Major design flaws can be detected and fixed early because critical modules tested first. In this type of method, we will add the modules incrementally or one by one and check the data flow in the same order.
In the top-down approach, we will be ensuring that the module we are adding is the child of the previous one like Child C is a child of Child B and so on as we can see in the below image:.
The bottom to up testing strategy deals with the process in which lower level modules are tested with higher level modules until the successful completion of testing of all the modules. Top level critical modules are tested at last, so it may cause a defect. Or we can say that we will be adding the modules from bottom to the top and check the data flow in the same order. In the bottom-up method, we will ensure that the modules we are adding are the parent of the previous one as we can see in the below image:.
In this approach, both Top-Down and Bottom-Up approaches are combined for testing. In this process, top-level modules are tested with lower level modules and lower level modules tested with high-level modules simultaneously. There is less possibility of occurrence of defect because each module interface is tested. We will go for this method, when the data flow is very complex and when it is difficult to find who is a parent and who is a child.
And in such case, we will create the data in any module bang on all other existing modules and check if the data is present. Hence, it is also known as the Big bang method. In this approach, testing is done via integration of all modules at once. It is convenient for small software systems, if used for large software systems identification of defects is difficult. Since this testing can be done after completion of all modules due to that testing team has less time for execution of this process so that internally linked interfaces and high-risk critical modules can be missed easily.
Let us see examples for our better understanding of the non-incremental integrating testing or big bang method:. Demo Swagger-ui-themes A collection of css themes to spice up your Swagger docs. Tools for previous Swagger versions The tools below do not produce Swagger 2. Eiffel Name Description swagger Swagger protocol implementation in Eiffel.
Doesn't depends on any framework Groovy Name Description springfox SpringFox Grails integration library that produces swagger specification documentation for Grails 3. Here is a demo application showcasing the library integration.
Includes client-side validation of requests against the given Swagger spec. Net Name Description ServiceStack a high-performance. Has support for Swagger integration. Net application that generates code or anything else, e. Swagger Validation A library to validate a request that integrates with swagger-node-express.
Includes detailed client-side validation against the API spec. Restler PHP framework, swagger support in 3. Api-doc Creates swagger docs from easily readable ascii text placed in the code. Depends on playframework , but may also be used in other frameworks. Swagger2Postman Creates a Postman collection from live Swagger documentation.
A template-driven engine to generate client code in different languages by parsing your Swagger documentation. SwagDoc is a Delphi library to generate swagger. Add swagger compliant specifications to your cowboy web server. PhoenixSwagger is the library that provides Swagger integration to the Phoenix web framework. Servant is a framework for building RESTful microservices in Haskell with first class Swagger support via servant-swagger.
Restlet Framework extension that supports auto-generation of Swagger 2. A maven build plugin which allows the codegen project to be triggered for generating clients, etc. Support Swagger Spec 2. From apigee. A tool for converting from other API specification formats e. A hapi. A mock server generated from an arbitrary Swagger file. Security testing will be covered in another section.
The entire rationale behind running tests is to find errors. That could take days or weeks, maybe months. The reason we do unit testing is to segregate the code to find and fix errors.
In the end, you will develop code that is more reliable and bug-free. Unit testing is agile. Old code will oftentimes need to be updated as new features are added.
By running tests on the new code, you will be able to determine whether or not the new code has broken an old feature. Testing frameworks are the software tools that help programmers write and run unit tests. It standardizes the way web applications are built by providing a foundation for testing along with the ability to execute tests and report results. Simply put, these testing frameworks make the lives of programmers so much easier.
Unit testing frameworks supply pre-written code and often include tools, libraries, compilers, and APIs. JUnit is one of the most widely adopted open source unit testing frameworks. TestNG is another popular open source unit testing framework, and many others provide more specific purposes. When conducting Java testing, test cases are generated for the source code. Java testing provides thorough and functioning test cases that can test every aspect of your application. A JUnit test case is exactly what it sounds like: a test scenario measuring functionality across a set of actions or conditions to verify the expected result.
JUnit is a simple framework to write repeatable tests. Those who are new to Java must learn to be efficient and optimize test cases while writing code. The test code is written to verify that the application works the way you want it to. With test-driven development, the unit test must be written and executed before any code is written.
Once the code is written, all tests should be executed and the code should pass. Tests should be executed each time any code is added to make sure nothing is broken. There are also features that allow you to peer code review process automation and run-time error detection for e. The GUI console for The Grinder allows you to have multiple load injectors to be monitored and controlled and Automatic management of client connections and cookies, SSL, Proxy aware and Connection throttling.
You can find more in depth information on The Grinders features here. It is freely available under a BSD-style open-source license. TestNG was primarily designed to cover a wider range of test categories such as unit, functional, end-to-end, integration, etc. It also introduced some new functionality that make it more powerful and easier to use, such as: Annotations, Running tests in big thread pools with various policies available, code testing in a multi thread safe, flexible test configurations, data-driven testing support for parameters, and more.
JUnit is a unit testing framework designed for the Java programming language. JUnit has played an important role in the development of test-driven development frameworks. It is one of a family of unit testing frameworks which is collectively known as the xUnit that originated with SUnit. You can find out more about JUnit on their website. JWalk is designed as a unit testing toolkit for the Java programming language.
It has been designed to support a testing paradigm called Lazy Systematic Unit Testing.
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