The method or process being used to implement automation is called a test automation framework. Several frameworks have been implemented over the years by commercial vendors and testing organizations. Automating tests with commercial off-the-shelf (COTS) or open source software can be complicated, however, because they almost always require customization. In many organizations, automation is only implemented when it has been determined that the manual testing program is not meeting expectations and it is not possible to bring in more human testers.
Authors Dorothy Graham and Mark Fewster wrote the field's seminal text, Software Test Automation, which has guided many organizations toward success. Now, in Experiences of Test Automation, they reveal test automation at work in a wide spectrum of organizations and projects, from complex government systems to medical devices, SAP business process development to Android mobile apps and cloud migrations.

A growing trend in software development is the use of unit testing frameworks such as the xUnit frameworks (for example, JUnit and NUnit) that allow the execution of unit tests to determine whether various sections of the code are acting as expected under various circumstances. Test cases describe tests that need to be run on the program to verify that the program runs as expected.
Sikuli is based on image recognition and has the capability of automating anything that we see on the screen. Currently, it supports desktop apps only which run on Windows, Mac or Unix/Linux. This tool is good at reproducing bugs quickly and its users have reported it to be very useful as compared other tools when you are going to automate an application which is not web-based.
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.
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Each of the above-mentioned testing tools offers some unique features that help to improve the quality of the released software.  You can choose any of these automation testing tools based on your project requirement. Apart from these automation testing tools, you require the right test management tool to get the desired results from your software testing. ReQtest is a test management tool that is preferred by the testers across the globe as it helps them to handle testing challenges and accomplish testing objectives easily.
With Ranorex Studio, every member of the team can build automated tests for desktop, web or mobile software with graphical user interfaces, regardless of programming ability. The Ranorex Recorder provides reliable capture-and-replay functionality for codeless creation of tests. Easily edit recorded actions, add text and image validations, set parameter values, and build data-driven tests without writing a single line of code. For users who prefer to build tests entirely in code, Ranorex Studio supports industry-standard programming languages C# and VB.NET with a comprehensive IDE that includes features such as intelligent code completion, debugging functionalities, refactoring mechanisms and more. For web application testing, Selenium WebDriver is built into the Ranorex core API, making it possible to create Selenium tests entirely within Ranorex Studio, without writing Selenium-specific code. Read more about our Selenium WebDriver integration.
Test automation on the other hand is the automated execution of predefined tests. A test in that context is a sequence of predefined actions interspersed with evaluations, that James Bach calls checks. These checks are manually defined algorithmic decision rules that are evaluated on specific and predefined observation points of a software product. And herein lies the problem. If, for instance, you define an automated test of a website, you might define a check that ascertains a specific text (e.g. the headline) is shown on that website. When executing that test, this is exactly what is checked—and only this. So if your website looks like shown in the picture, your test still passes, making you think everything is ok.
Some software testing tasks, such as extensive low-level interface regression testing, can be laborious and time-consuming to do manually. In addition, a manual approach might not always be effective in finding certain classes of defects. Test automation offers a possibility to perform these types of testing effectively. Once automated tests have been developed, they can be run quickly and repeatedly. Many times, this can be a cost-effective method for regression testing of software products that have a long maintenance life. Even minor patches over the lifetime of the application can cause existing features to break which were working at an earlier point in time.
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While automated testing has been considered essential for organizations, both large and small, to implement in order to deliver outstanding software and stay competitive in the industry, it can be tough to get started. Outlining an effective roadmap, building robust frameworks, choosing the right tools, and measuring the potential monetary impact that automation could have on your delivery lifecycle are all critical components of any successful automated testing strategy, but each step presents its own challenges and costs.
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But if test automation is so limited, why do we do it in the first place? Because we have to, there is simply no other way. Because development adds up, testing doesn’t. Each iteration and release adds new features to the software (or so it should). And they need to be tested, manually. But new features also usually cause changes in the software that can break existing functionality. So existing functionality has to be tested, too. Ideally, you even want existing functionality to be tested continuously, so you recognise fast if changes break existing functionality and need some rework. But even if you only test before releases, in a team with a fixed number of developers and testers, over time, the testers are bound to fall behind. This is why at some point, testing has to be automated.
Automated testing is, well, automated. This differs from manual testing where a human being is responsible for single-handedly testing the functionality of the software in the way a user would. Because automated testing is done through an automation tool, less time is needed in exploratory tests and more time is needed in maintaining test scripts while increasing overall test coverage.
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See below for a list of popular unit testing frameworks and tools for major platforms and programming languages. These frameworks can be used by programmers to test specific functionality in libraries and applications. Unit tests can then be used to automatically test new versions and builds as part of an automated build system or deployment process.

The takeaway is that testing is a process requiring human intervention. Bas Dijkstra, an experienced test automation consultant, describes how even the term “test automation” is flawed unless you understand what is and isn’t automated. The actual “learning, exploring, and experimenting” involved in manual, human-performed testing cannot be automated, according to Dijkstra. He writes:


While automation saves you a lot of time, it still takes time. You can't run all your tests all the time. It takes too long and would generate an unmanageable analysis and maintenance effort. In my group, we've taken both manual and automation testing to three levels: sanity, end-to-end, and full. In addition to our feature tests, on every code commit, we run a set of high level, cross-feature tests to make sure that a code change in one feature hasn't broken another one. Only then do we run a set of more extended tests specific to the feature for which the code was committed. Then, we run our suite of feature-level sanity tests on our continuous delivery environment every three hours to make sure all features are in good shape. We only do this on one browser though, because we've found that if a test fails, it doesn't usually depend on the browser. Finally, we run feature end-to-end testing on our nightly environment.

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