Realizing the benefits of software automation testing first requires understanding that automation isn’t automatic. If you understand the basics — what it is, what it is not, who uses it and why they do so — you will start to see why automation testing is fundamental to modern software development. The efficiency gains associated with successful test automation require the use of automation frameworks and proper automation software tools.
This approach works fine for the first weeks, when running checks only takes five minutes. Over time, though, five minutes turn into an hour, then two, then three. Before you know it, testing locks up the tester's computer or test environment all afternoon. So you start kicking off automated test runs at 5 am or 5 pm and get the results the next day. Unfortunately, if something goes wrong early on, all the results will be corrupted. That slows to a crawl the feedback loop from development to test, creating wait states in the work.
The increased demand for automation is trending in our software testing industry, as well. If you check out any software or application testing communities (i.e., uTest, Quora, etc.), you will find software testers urging for various tools that can be helpful in their day to day testing activities, whether it is for desktop testing, web testing, browser testing, regression testing, web services and API testing, and many more.
Jones believes the most common reason for using test automation today is to shorten the regression test cycle. Regression tests are used to determine if changes to the software are the cause of new problems. They verify that a system under test hasn’t changed. To guard against introducing unintended changes, they become part of a regression test suite after the tests pass. Regression tests are automated to ensure regular feedback.
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Considering all of its shortcomings, we are lucky that testing existing functionality isn’t really testing. As we said before, real testing is questioning each and every aspect and underlying assumption of the product. Existing functionality has already endured that sort of testing. Although it might be necessary to re-evaluate assumptions that were considered valid at the time of testing, this is typically not necessary before every release and certainly not continuously. Testing existing functionality is not really testing. It is called regression testing, and although it sounds the same, regression testing is to testing like pet is to carpet—not at all related. The goal of regression testing is merely to recheck that existing functionality still works as it did at the time of the actual testing. So regression testing is about controlling the changes of the behaviour of the software. In that regard it has more to do with version control than with testing. In fact, one could say that regression testing is the missing link between controlling changes of the static properties of the software (configuration and code) and controlling changes of the dynamic properties of the software (the look and behaviour). Automated tests simply pin those dynamic properties down and transform them to a static artefact (e.g. a test script), which again can be governed by current version control systems.
Cucumber is a tool for working with the executable specifications. The executable specifications are used for greater collaboration among IT and business teams. This tool is useful for writing acceptance tests for the web application. Cucumber offers feature files that can be used as a go-to-documents by Business Analysts, Developers, and Testers, etc. Initially, Cucumber was implemented in Ruby language but later it was extended to the Java framework. Cucumber supports languages such as Perl, PHP, Python, Net etc.
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Building a successful automated testing strategy is tough and the approach will vary on a team-by-team basis. No team is completely identical to another. Some may consist of more manual testers than automation engineers, while some may have shifted left and depend on developers to do the heavy lifting. Budget, deadlines, application type, and development model are all factors that impact how an automated testing strategy should outlined be implemented.
An important part of UI testing is verifying typical use cases. For example, a typical use case for a hotel booking website includes searching for an available room, selecting one, entering reservation details, and confirming the booking. When the test should be successful for the data values provided, it is called a “happy path scenario.” Functional testing also validates the behavior of the application when no rooms are available for the desired date (the “sad path”) as well as when the user enters out-of-range dates for a reservation or an invalid credit card number (the “bad path”). Ranorex Studio’s data-driven testing automates the process of repeating a test for multiple data values so you can effortlessly cover the happy path, sad path, and bad path. Data values can be retrieved from an internal data table, external Excel file or SQL table. Since the test data is stored separately from the test procedure, adding or changing scenarios is a snap. For more complex scenarios, Ranorex Studio supports local and global parameters, keyword-driven testing, and conditional test execution.
Automation testing is much faster than its human equivalent, and yields crucial analytics. It lets us run tests 24-7, even several at once. Perhaps most crucially, it enables us, as developers, to focus on the creative stuff, freeing us up for what’s most important. Unfortunately there are a baffling number of automated mobile app testing tools to choose from, and each one comes with its own bullish marketing literature, telling you that this product is more reliable than any other. Given the baffling amount of jargon and technical-speak involved, it’s hard to separate the real from the spiel.
Tools are specifically designed to target some particular test environment, such as Windows and web automation tools, etc. Tools serve as a driving agent for an automation process. However, an automation framework is not a tool to perform a specific task, but rather infrastructure that provides the solution where different tools can do their job in a unified manner. This provides a common platform for the automation engineer.