![]() ![]() This may help locate errors when your application results in unexpected output while no logical errors are detected in your code, and you suspect that the bottleneck is the interaction with the web service. During development, you may also call this web service from outside your application. In this case, it is helpful to investigate the access to the service and the required input data before you start the development. When you are developing an application that addresses a RESTful web service. When you are developing a RESTful web service and want to make sure it works as expected, is accessible in compliance with the specification, and responds correctly. There are two main use cases when you need to compose and run HTTP requests: When you take your test from functional tests to load tests, you get a whole set of API testing capabilities and functionality that you would not get in any other tool in the market.With the HTTP Client plugin, you can create, edit, and execute HTTP requests directly in the IntelliJ IDEA code editor. Linking data elements from Excel, CSV and databases to the parameters in JSON/ XML.Transfer properties, parameters, from one response with other requests or similar requests.Method chaining between different kinds of API test cases.Refactoring APIs with definition changes.Working with JSON and XML through point and click tools.SoapUI and LoadUI are API testing tools that enable you to do a lot of things with your APIs, like: In just a few clicks, you can reuse your existing functional tests (from SoapUI or ReadyAPI) as load tests. If you have already written a functional test case, you can quickly take those functional test case to the next step and convert it to a load test. ReadyAPI makes it very easy for testers, or developers to create a load test from endpoints, API specifications and definitions. So, What Is This Concept of Scriptless Load Testing? This now requires team leaders and managers to establish a process for coding standards on scripts and have someone review all the scripts to make sure they are meeting these standards.Ĭheck-in and check-out needs to be monitored and at the end of the day, there’s a lot of time, resources and overhead that gets into solutions that are primarily script based. This ends up causing challenges when a new tester joins the team and tries to decipher what’s written in these scripts that have so many comments and edits on them. ![]() They add their own functions or procedures in those scripts. It’s also true that every developer or tester who is working on those scripts leaves their own fingerprints on them.Įveryone likes to do things their own way. If you’re only load testing a single API this is fine, but as the number of APIs you want to test grows from two to five to 100, the number of scripts scales upwards as well – and you’re left working and maintaining scripts all day. With script-based tools, most of your time is going to be spent in creating and maintaining scripts. What if the code doesn’t run the first time?ĭo you think you will have the expertise to debug and run it in a short amount of time?ĭo you want to maintain these scripts and manage the complexity as these scripts bloat in size? Reuse Your Functional Tests That script will then run on a system that will generate the load using the code that you just wrote. If you work with solutions which are open source or a big-name load testing solution, you can expect to create an API test that will be backed with a script.Īlthough these systems claim that no scripting experience is required, at the end of the day, every action you take and every test case you create generates a script. Therefore, a test case meant for a frontend API has a lot of functionality lost in translation when translated to backend APIs. These script-based platforms are designed to record UI transactions, not APIs. Things like parsing a JSON path, parsing XML, chaining two API requests into a sophisticated scenario and validating API schema are not native capabilities built in these tools. On the flip side, performance focused testing solutions like LoadRunner and JMeter are focused on UI testing and require a lot of custom coding when it comes to endpoints and APIs. Additionally, tools like REST-Assured and Postman do not scale on functionality, test cases, or capacity when you use them for performance testing. While these are acceptable starting points, they’re not a true end-end test when it comes to functional testing. When it comes to testing APIs, many people take a straightforward approach and run basic functional tests or explore an endpoint through a browser. ![]()
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