Top 10 Test Automation Frameworks in 2020

Suyash Dubey
By Suyash Dubey
August 17, 2020
11 min Read
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Top 10 Test Automation Frameworks in 2020

We are moving toward a future where everything is going to be autonomous, fast and highly efficient. To match the pace of this fast-moving ecosystem, application delivery times will have to be accelerated, but not at the cost of quality. Achieving quality at speed is imperative and therefore quality assurance gets a lot of attention. To fulfill the demands for exceptional quality and faster time to market, automation testing will assume priority. It is becoming necessary for micro, small, and medium-sized enterprises (SMEs) to automate their testing processes. But the most crucial aspect is to choose the right test automation framework. So let’s understand what a test automation framework is.

What is a Test Automation Framework?


A test automation framework is the scaffolding that is laid to provide an execution environment for the automation test scripts. The framework provides the user with various benefits that help them to develop, execute and report the automation test scripts efficiently. It is more like a system that was created specifically to automate our tests. In a very simple language, we can say that a framework is a constructive blend of various guidelines, coding standards, concepts, processes, practices, project hierarchies, modularity, reporting mechanism, test data injections etc. to pillar automation testing. Thus, the user can follow these guidelines while automating applications to take advantage of various productive results.

The advantages can be in different forms like the ease of scripting, scalability, modularity, understandability, process definition, re-usability, cost, maintenance etc. Thus, to be able to grab these benefits, developers are advised to use one or more of the Test Automation Framework. Moreover, the need of a single and standard Test Automation Framework arises when you have a bunch of developers working on the different modules of the same application and when we want to avoid situations where each of the developers implements his/her approach towards automation. So let’s have a look at different types of test automation frameworks.

Types of Automated Testing Frameworks


Now that we have a basic idea about Automation Frameworks, let’s check out the various types of Test Automation Frameworks available in the marketplace. There is a divergent range of Automation Frameworks available nowadays. These frameworks may differ from each other based on their support to different key factors to do automation like reusability, ease of maintenance etc.

Types of test automation frameworks:

  1. Module Based Testing Framework
  2. Library Architecture Testing Framework
  3. Data Driven Testing Framework
  4. Keyword Driven Testing Framework
  5. Hybrid Testing Framework
  6. Behavior Driven Development Framework
  7. types of automation frameworks

Benefits of a Test Automation Framework


Apart from the minimal manual intervention required in automation testing, there are many advantages of using a test automation framework. Some of them are listed below:

  1. Faster time-to-market: Using a good test automation framework helps reduce the time-to-market of an application by allowing constant execution of test cases. Once automated, the test library execution is faster and runs longer than manual testing.
  2. Earlier detection of defects: The documentation of software defects becomes considerably easier for the testing teams. It increases the overall development speed while ensuring correct functionality across areas. The earlier a defect is identified, the more cost-effective it is to resolve the issue.
  3. Improved Testing efficiency: Testing takes up a significant portion of the overall development lifecycle. Even the slightest improvement of the overall efficiency can make an enormous difference to the entire timeframe of the project. Although the setup time takes longer initially, automated tests eventually take up a significantly lesser amount of time. They can be run virtually unattended, leaving the results to be monitored toward the end of the process.
  4. Better ROI: while the initial investment may be on the higher side, automated testing saves organizations many a lot of money. This is due to the drop in the amount of time required to run tests, which leads to a higher quality of work. This in turn decreases the necessity for fixing glitches after release, thereby reducing project costs.
  5. Higher test coverage: In test automation, higher number of tests can be executed pertaining to an application. This leads to a higher test coverage, which in a manual testing approach would imply a massive team, limited heavily with their amount of time. An increased test coverage leads to testing more features and a better quality of application.
  6. Reusability of automated tests: The repetitive nature of test cases in test automation helps software developers to assess program reaction, in addition to the relatively easy configuration of their setup. Automated test cases can be utilized through different approaches as they are reusable.

Top ten test automation frameworks


1. Robot Framework
Robot Framework is the best choice if you want to use a python test automation framework for your test automation efforts. The Robot Framework is Python-based, but you can also use Jython(Java) or IronPython(.NET). The Robot Framework uses a keyword-driven approach to make tests easy to create. Robot Framework can also test MongoDB, FTP, Android, Appium and more. It has many test libraries including Selenium WebDriver library and other useful tools. It has a lot of API’s to help make it as extensible as possible. The keyword approach used by Robot Framework is great for testers who are already familiar with other vendor-based, keyword-driven test tools, making the transition to open source much easier for them.

2. WebdriverIO
WebdriverIO is an automation test framework based in Node.js. It has an integrated test runner and you can run automation tests for web applications as well as native mobile apps. Also, it can run both on the WebDriver protocol and Chrome Devtools protocol, making it efficient for both Selenium Webdriver based cross-browser testing or Chromium based automation. As WebDriverIO is open source, you get a bunch of plugins for your automation needs. ‘Wdio setup wizard’ makes the setup simple and easy.

3. Citrus
Citrus is an open-source framework with which you can automate integration tests for any messaging protocol or data format. For any kind of messaging transport such as REST, HTTP, SOAP, or JMS, Citrus framework will be suited for test messaging integration. If you need to interact with a user interface and then verify a back-end process, you can integrate Citrus with Selenium. For instance, if you have to click on a “send email” button and verify on the back end that the email was received, Citrus can receive this email or the JMS communication triggered by the UI, and verify the back-end results, all in one test.

4. Cypress
Cypress is a developer-centric test automation framework that makes test-driven development (TDD) a reality for developers. Its design principle was to be able to package and bundle everything together to make the entire end-to-end testing experience pleasant and simple. Cypress has a different architecture than Selenium; while Selenium WebDriver runs remotely outside the browser, Cypress runs inside of it. This approach helps in understanding everything that happens inside and outside the browser to deliver more consistent results. It does not require you to deal with object serialization or over-the-wire protocols while giving you native access to every object. Cypress can synchronously notify you of every single thing that happens inside the browser as you’re pulling your app into it, so that you have native access to every DOM element. It also makes it easy to simply drop a debugger into your application, which in turn makes it easier to use the developer tools.

5. Selenium
One of the most popular open source test automation frameworks for web apps. Selenium also serves as a base for a lot of other testing tools as it has cross-platform and cross-browser functionality. Selenium supports a wide range of programming languages such as Java, C#, PHP, Python, Ruby, etc. It is easy to maintain as it has one of the largest online support networks. Selenium is highly extendable through a wide range of libraries and APIs to meet everyone’s needs and requirements. Selenium is preferred by testers as it is possible to write more advanced test scripts to meet various levels of complexity. It provides a playback tool for test authoring without the need to learn a specific scripting language.

6. Cucumber
It is a cross platform behavior driven development (BDD) tool which is used to write acceptance tests for web applications. Cucumber is quick and easy to set up an execution and allows reusing code in the tests. It supports languages like Python, PHP, Perl, .NET, Scala, Groovy, etc. Automation of functional validation in easily readable and understandable format. One good feature is that both specification and test documentation are uploaded in a single up-to-date document. Cucumber makes it easy for the business stakeholders, who are not familiar with testing, as they can easily read the code as test reports are written in business readable English. The code can be used together with other frameworks like Selenium, Watir, Capybara, etc.

7. Gauge
It is an open source tool agnostic test automation framework for Mac, Linux and Windows. People who work on TDD and BDD will appreciate Gauge’s focus on creating living/executable documentation. Specs – the Gauge automation tests are written using a markdown language with C#, Java and Ruby within your existing IDEs like Visual Studio and Eclipse. Gauge’s functionality can also be extended with its support of plugins. It was developed as a BYOT (Bring Your Own Tool) framework. So you can use Selenium or you can use anything else for driving your tests UI or API tests. If you want a readable non-BDD approach to automation, you should try Gauge.

8. Serenity
If you are looking for a Java-based framework that integrates with behavior-driven development (BDD) tools such as Cucumber and JBehave, Serenity might be the tool for you. It’s designed to make writing automated acceptance and regression tests easier. It also lets you keep your test scenarios at a high level while accommodating lower-level implementation details in your reports.

Serenity acts as a wrapper on top of Selenium WebDriver and BDD tools. It abstracts away much of the boilerplate code you sometimes need to write to get started which makes writing BDD and Selenium tests easier. Serenity also offers plenty of built-in functionality, such as handling running tests in parallel, WebDriver management, taking screenshots, managing state between steps, facilitating Jira integration, all without having to write a single line of code.

9. Carina
Carina is built using popular open-source solutions like Appium, TestNG and Selenium, which reduces dependence on a specific technology stack. You can test mobile applications (native, web, hybrid), WEB applications, REST services, and databases. Carina framework supports different types of databases like MySQL, SQL Server, Oracle, PostgreSQL, providing amazing experience of DAO layer implementation using MyBatis ORM framework. It supports all popular browsers and mobile devices and it reuses test automation code between IOS/Android up to 80%. API testing is based on the Freemarker template engine and it provides great flexibility in generating REST requests. Carina is cross-platform and tests may be easily executed both on Unix or Windows OS.

10. EarlGray
Developers often face difficulty with some of the existing test automation framework in synchronization of the app and the instrumentation. Also, executing tests on apps as synchronized and advanced only when UI elements are visible on the screen has caused issues for many developers. Google EarlGrey has built-in synchronization that makes test scripts wait for UI events to occur before the script tries to interact with the UI of the app. This type of implementation makes the test script concise as all steps of the test script shows how the test will proceed and UI gets synchronized with it. One more key aspect of EarlGrey is that all actions on UI elements happen only on visible elements. This provides a fast and robust approach to ensure UI testing goes through as clicks, gestures and other user interactions do not get done if the UI element is not fully shown.

In a nutshell


This list of top tools here represents the best tools that are mature, popular, and provide test automation capabilities using AI/ML to address the challenges that organizations are now facing to deliver Quality at Speed. This list also includes the tools that provide API and services testing which is essential for successful DevOps transformation. The emerging technologies like AI, codeless, big data and IoT testing, are making test automation more efficient while creating opportunities for the existing tools and new players to assert value to the testing communities.

The choice of automation tools should not only meet your current needs but should also focus on potential trends and improvements. An efficient test automation tool should support basic optimization, data generation, smarter solutions, and analytics. As of now, the level of test automation in organizations is low at between 14% and 18%. But organizations are working towards increasing the automation coverage upto 80%. API and services testing is also a trend that should see further development in the future.

Suyash Dubey
Suyash Dubey

Suyash is a content strategist at pCloudy. He is a frequent contributor to the world's leading mobile technology blogs and tech forums. In his spare time, you will find him reading detective novels, watching a documentary or exploring a new destination.

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Remote working is going to be a new normal and remote access tools and platforms will play a key role in maintaining productivity. Working from home has many advantages both for enterprises and teams. There are many tools that help teams to collaborate and share all the information conveniently over the net. pCloudy is one such tool that gives you remote access to hundreds of real devices to test your app.

So let’s look at the 10 ways how pCloudy could help in maintaining business continuity while working remotely.

1. Remote access to devices: Test your apps from home by accessing remote devices on pCloudy. You don’t have to worry about touching or managing the devices.

Remote access to devices

2. Device access to geographically distributed teams: Since testing professionals are working remotely, the problem is sharing the limited number of devices for app testing among the team members. With pCloudy offering a range of devices over cloud, members across different locations can access hundreds of real devices on the cloud for their app testing needs.

Device access to geographically distributed teams
3. All in one: Manual and automation testing can be performed remotely on real devices. The platform is well suited for continuous testing and optimizes your DevOps process.

4. Autonomous testing bot: use our AI power autonomous testing bot to minimize the effort and time spent on testing.

Autonomous testing bot
5. Team management: Manage platform access to the team members and share detailed app test reports.

Team management
6. Parallel testing: Run automation tests in parallel on multiple devices to increase the testing efficiency.


7. Latest devices: No need to wait for the delayed shipments of the new devices as all the latest devices are available on pCloudy.

8. Fully integrated: pCloudy is integrated with most of the popular tools and frameworks used for task management, version control, test automation, etc.

Fully integrated
9. Device tunnel: Developers can use features like Device tunnel to access devices in their Dev environments like Android Studio or Xcode

Device tunnel
10. Quality support: Achieve quality@speed in mobile app testing while working from home. Our technical support team will be available to help you 24/7.

11. Device management: Hassle-free app testing for our users and our cloud infra team will take care of the continuous availability and maintenance of the devices.

It has been speculated that around 30% of the service sector workforce across the globe will be working from home by 2030. You can stay ahead of others in this initiative and adopt flexible work preferences. Contact us if you need more information on how pCloudy could help in enhancing productivity while working from home.

Suyash Dubey
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5 Ways AI is Changing Test Automation

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5 Ways AI is Changing Test Automation

Software testing has evolved a lot since the time when the waterfall model was used. All the work was done in a sequential manner and only after the development phase was complete the testers used to test the product. Testers used to find bugs but a lot of time and energy was wasted in the process to rebuild and code again.

Now companies are using an Agile model where the main goal is to find the bugs in continuous development, fix them quickly and release the app faster. There is a need to improve the automated testing process to complement the manual testing. More emphasis has been given to CI, CD, and DevOps to make the software development effective.

There has been a considerable change in the functioning of testing tools and test automation frameworks. The most important change is the introduction of AI in a test automation strategy.

According to G2Crowd, AI-powered bots are expected to cut business cost by $8 billion by 2022. Testing bots are already empowering automation testing and will play a major role in reducing the time and effort spent in mobile app testing.

Let’s have a look at how AI is breaking new ground for test automation.

1. Running automated tests that matter

It’s not a good strategy to run your entire test suite due to a very small change in your app that you couldn’t trace. You are probably already generating a lot of data from your test runs if you are doing continuous integration. But it will take a lot of time to go through the data and search for common patterns. So you need to know if you make a small change in code then what is the minimum number of test you need to run to figure out if the change is needed or not.

2. Reducing maintenance and eliminating flaky test

We can run several automated tests on a daily basis to ensure the functionalities of the app are still stable. Although, if we find out that half of this test failed. In that case, we would need to spend a lot of time to troubleshoot the failures and investigate the cause. Then there is a need to find ways to fix the failures and then work on the changes.



software maintainance

Using AI we can avoid issues and start detecting issues in the test before they even occur. So instead of reacting to it, we can proactively fix tests. AI can figure out which tests are stable or flaky based on the number of test runs and it can tell us what test needs to be modified to ensure test runs are stable. AI can also handle test running on different resolutions and can optimize the wait time used in the test to wait for the page to load.

3. Dependencies on other modules

Writing a test for systems having dependencies on other modules is also a challenge. AI can help us to mock responses from a database or server. The AI can start recording server responses once we have written the test and have run them for a period of time. So the next time we run the test it will access the stored responses and will continue to run without any obstacles. This will speed up the process as the delay in response is eliminated and the server or physical database is no more needed.

4. Learning from production data

Real user data can be used to create an automated test and with the help of AI, we can observe and learn how the customer is using our product. We can identify common actions such as search option, using filters, login/logout, etc and compile them into reusable components. These components can be used for our test as well. Therefore, we have an actual test written by AI based on the real data along with the reusable components.

5. Easy execution of tests and speeding up the release

In automation testing, the time and effort it takes to write and execute a test is a major challenge due to the complexity of the test automation tools, app, and programing language used. To mitigate these problems AI-based tools are being used. The use of dynamic locators and reusable components has made it possible to write and execute a test in hours which earlier used to take a week.

Conclusion

The DevOps theory says test early, test often, but this puts a lot of responsibility on the testing team. Also, it’s not feasible for testing teams to spend time to do exploratory testing manually for each new release. AI-based tools can perform codeless automation testing which will save us time and resources and give the testers some space to breathe.


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  • Suyash Dubey
    Suyash Dubey

    Suyash is a content strategist at pCloudy. He is a frequent contributor to the world's leading mobile technology blogs and tech forums. In his spare time, you will find him reading detective novels, watching a documentary or exploring a new destination.

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    pCloudy Among Top 3 Test Automation Software

    shivani
    By shivani
    July 6, 2018
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    pCloudy Among Top 3 Test Automation Software

    pCloudy Among Top 3

    We are proud to announce that pCloudy has been ranked among the top 3 Test Automation Software products based on the user satisfaction. With this, we have got another feather added in our cap after achieving the 50k milestone. It has become possible only because of your constant trust and support that motivates us to keep growing stronger.

    Check out this list of the top Test Automation Software products based on user satisfaction. As per G2Crowd, the product’s satisfaction score is calculated by a proprietary algorithm that factors in real-user satisfaction ratings from review data. Check yourself.

    Top 15 Test Automation Testing Platforms

    shivani
    shivani

    She is a Product Marketer with over 9 years of diversified experience across content, branding, and product marketing. Her experience ranges from global brands to nimble startups. She is a custodian of Brand & Content, telling stories about the brand that delights customers and provides compelling business value.

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