Top 10 Automation Testing Tools For 2019

According to the World Quality Report 2018–19 the low level of automation of test activities has turned out to be a critical bottleneck in the further evolution of Quality Assurance & testing. Making use of suitable test automation tools at the right time is crucial to deliver a high- quality product at a fast pace. These tools ensure that the advantages of automation are delivered to the fullest. Automation testing tools are a crucial part of the software development process.

With a variety of open source and commercial test automation tools, selecting the best automation testing tool can become an arduous task. Here is a curated list of best-automated testing tools –these automation testing tools included in this list are selected from three major criteria:

  • Popularity and maturity
  • Supporting API & services testing
  • Offering some Artificial Learning and Analytics Capabilities

1.Selenium

  • Topping the list, Selenium is an outstanding automated software testing tool for testing web applications that is accessible today in the market
  • It automates across multiple browsers like Firefox, Chrome, IE, etc. and enables users to sail through several browser-specific testing purposes. The test script can be easily written in programming languages such as Python, Java, Ruby, C#, PHP, JavaScript and Perl
  • Companies prefer Selenium this automation testing tool as the best one that can be integrated with automated testing frameworks and is compatible with various programming languages.

2. TestComplete

  • It is a SmartBearproduct, an extraordinary test automation tool for mobile, web, and desktop testing. TestComplete is an open test platform that can also be integrated effortlessly with other products contributed by SmartBear
  • TestComplete can also help you create robust, reusable, and automated tests across the web, desktop, mobile, and many devices effectively and easily
  • Silverlight apps can also be tested using TestComplete. It allows testers to create automated tests for iOS, Web, Microsoft Windows, and Android apps.
  • This amazing test automation tool can perform parallel regression testing with automation builds & create steady regression tests

3.Katalon Studio

  • This is an incredible test automation solution for a mobile, web application and web services. Being built on top of the Appium and Selenium frameworks, this tool takes benefits of these solutions for integrated software automation
  • Katalon Studio tool supports various levels of testing skill set. Even Non-programmers can also find it trouble-free to start the test automation project (such as using Object Spy to record testing scripts) while programmers and advanced testers can save time from building new libraries and managing their scripts
  • Katalon Studio can be incorporated into CI/CD processes and performs well with well-admired software testing tools in the QA process counting JIRA, qTest, Git, and Jenkins.
  • Additional features like Katalon Analytics can provide users the comprehensive status of test execution reports through dashboard comprising graphs, metrics, and charts

4.Unified Functional Testing (UFT)

  • UFT is a famous commercial test automation tool for Functional Testing
  • It gives a comprehensive feature set for web services, API, and GUI testing of web, desktop, and mobile apps across varied platforms
  • The is an amazing tool and it has improved reusable test components, image-based object recognition feature, and automated documentation
  • Unified Functional Testing uses Visual Basic Scripting Edition to register automation testing processes and object control. It is integrated with Mercury Quality Center and Mercury Business Process Testing. UFT tool also supports CI thorugh integration with CI tools like Jenkins

5.SoapUI

  • SoapUI is a web service testing tool for Representational State Transfers (REST) & Service-Oriented Architectures(SOA)
  • This automation testing tool is an open source that allows automated functional testing, automated load testing, and compliance testing.
    SoapUI additionally comprises mocking and simulation traits together with web service research
  • It isn’t an automation tool for Web or mobile app testing; however, it can be a great tool to test API & services
  • SoapUI is a headless functional testing tool perfectly designed for API testing. API automation testers can use either the pro edition or open source. The pro version has a user-friendly interface as well as various advanced features like form editor, assertion wizard, and SQL query builder

6.Cucumber

  • This is a famous open source BDD (Behavior Driven Development) tool. Cucumber supports languages such as Java, Ruby, Groovy, Scala, etc
  • Drafting automation test scripts is a joint effort of the developer, testers, and customers. Cucumber supports only the web environment. Test code is written in easy English called Gherkin. Cucumber code can be executed on several test automation frameworks such as Selenium, Ruby, etc


7. IBM Rational Functional Tester

  • It is commercial automated testing tool from IBM. It supports extensive ranges of development environments such as Flex, PowerBuilder, Siebel, SAP, Java, Dojo, and Net amongst others.
  • RFT supports two scripting language VB.Net and Java. Rational Functional Tester (RFT) tool supports regression testing, functional testing, & Data-driven testing.
  • RFT’s other crucial feature is its integration with IBM Jazz apps lifecycle management systems like Rational Quality Manager and IBM Rational Team Concert


8. Tricentis Tosca

  • Tricentis Tosca is a model-based automated testing tool that provides a comprehensive feature set for continuous test comprising analytics, dashboards, and integrations to support DevOps and Agile methodologies.
  • Tricentis Toscaa assists users to optimize the reusability of test assets. Like several other automation testing tools, this test automation tool supports an extensive range of technologies and apps like API, web, and mobile
  • This test automation tool also has exclusive features for risk analysis, integration management, and distributed execution

9. Postman

  • This amazing tool is another automation tool perfectly designed for API testing. Users can install this tool as a browser extension or a desktop app on Windows, Mac, and Linux.
  • Postman is one of the priorities not only among testers for API test automation but also software developers who use the tool to develop and test APIs.

10. Ranorex

  • Ranorex is an incredible commercial automation tool for desktop, web, and mobile testing. This popular tool features advanced traits for GUI recognition, record/ playback, and reusable test scripts.
  • Codeless test creation is one such beneficial feature of this automation tool that allows new testers to learn and apply automation testing to their projects.
  • This advanced automation testing tool also supports Selenium integration for web app tests. Testers can distribute the execution of their automation tests across browsers and platforms using Selenium Grid. Ranorex offers a low-pricing model for enterprises.

The automated tests tools listed above will slash the time spent and further support companies by saving loads of resources. Your choice of automated testing tools should not only meet your current requirements but should also focus on potential trends. With these significant automation testing tools, the enterprises can ensure that all the products delivered are free of any bug and glitches.

You cannot find any real-world software 100% free of flaws or bugs. The best approach is to thoroughly test the software and fix it whenever found. You need an expert and adept software QA testing team you can trust to do that. We at ImpactQA are that team. Contact us; we will be glad to help you.

Top Software Testing Trends in 2019

The introduction of new technologies has brought the current updates in the software design, development, software testing & delivery. There has been great progress in the software testing field with new software testing trends coming into IT industry services. Quality Assurance and Software testing have come a long way. From a gate-keeping quality approach to an active, more evolved, “fit-for-purpose” strategic role, QA is now quality engineering in a true sense.

Digital transformation is yet another significant point of focus for the industries and the enterprises are ranking high on cloud computing, big data, business analytics and. With the advent of DevOps and Agile development technologies, the software development business is undergoing major interference. The new addition is the agile methodology adoption to undertake a digital transformation. Agile methodology aids to align digital transformation initiatives with business requirements.

As we head into 2020, we can expect to reach critical milestones as various new software testing trends take hold. Are you ready to explore these trends in software testing? Here are the top software testing trends 2019 the ImpactQA team expects to see take shape in the year ahead:

1- Quality Assurance Shifts to Quality Engineering- Quality Assurance is now a complex field that covers a wide range of technology and skills. From automation testing and DevOps to pipeline integration, QA has evolved well beyond its initial scope. To keep pace with this evolution, we’ll see a strong shift from QA to quality engineering.

2- Increasing adoption of Agile & DevOps– To keep pace with this growth, enterprises are not looking at having centralized Test Centers of Excellence any longer. The erstwhile testing arena is making a shift towards quality engineering, & software testing is intended to become progressive, iterative, and flawlessly integrated with development.

3- High Level of Test Automation- According to a current study on automation testing trends, 44% of businesses expect to automate 50% or more of testing in 2020. Organizations see several benefits, counting improved test coverage, faster software testing cycles, and the ability to catch defects earlier. To maximize the scalability of test automation even, ‘Script-less Test Automation’ is introduced.

4- Big Data Testing- There is varied types of software testing in Big Data projects like Database testing, Infrastructure, Functional Testing, and Performance testing. Big Data defined as a high volume of data unstructured or structured. The quality of data is also a significant factor in big data testing. The data quality is checked on account of various traits like accuracy, conformity, validity, consistency, data completeness, duplication, etc.

5- IoT Testing- Gartner estimates the number of IoT devices worldwide will reach approximately 20.4 billion by the year 2020. Hyper-connectivity is taking across the globe and the number of connected devices is estimated to be 1 trillion (by the year 2025). IoT test approaches have also emerged & necessitated a varied set of tools and techniques altogether. The focus is on connectivity, usability, security, performance, and compatibility testing. The variety of testing for IoT systems are:

  • Compatibility Testing
  • Performance Testing 
  • Usability Testing
  • Reliability & Scalability Testing
  • Data Integrity Testing
  • Security testing

6- Performance Testing Shifts to Performance Engineering- Performance testing will be replaced by performance testing. Rather than executing test scripts, the focus will be on analyzing how each component of the system work together. The variety of elements of the system comprises security, performance, hardware, usability, software, configuration, business value, and the client. Performance engineering will assist in exceeding client expectations in 2020.

7- Robotic Process Automation (RPA)– Latest and new-edge technologies, like cognitive computing, the Internet of Things (IoT), Artificial intelligence (AI), and machine learning are revolutionizing all domains. Progress in software and Artificial Intelligence world has paved the way for Robotic Process Automation (RPA). It is the latest technology which can re-invent the business process management landscape.

Organizations face countless software testing challenges and choices these days as technology evolves and the digital economy grows. Adopting the right software testing trends, tools and processes will help organizations to stay competitive or on top of their game. Embrace the change, and lead the way to a better-progressive future.

5 Ways AI is Shaping the Future of Software Testing

Artificial Intelligence is the hottest buzzword these days and advancement in AI allows Enterprise and industries to make smart decisions and radically transform processes. As software tests shift gears from manual to automation for embracing the speed for DevOps and digital transformation, Artificial Intelligence has emerged to be the key lever for this change.

AI working ways
AI working ways

Applications today interact with other apps through APIs, they leveraging legacy systems, and they grow in the complex from one day to the next in a nonlinear fashion. What does that mean for experts? The recent World Quality Report declared that it will help. It is now believed that the most significant solution to overcome increasing QA Challenges will be the rising trend and introduction of machine-based intelligence.

Software testing is an imperative process that makes sure client satisfaction in the app. It is fundamentally about inputs and anticipated results that blend a big amount of human as well as machine-generated data. And so, the test is a ready ground for AI.

Whether automated or manual, software testing can benefit greatly from using it, BOTs, as well as the intelligence, derived data & analytics. Test bots run automated tasks (scripts) over the Internet & perform repetitious actions. Test bots (Voice Bots and Chat Bots) also interpret, mimic and react to the written and spoken the language. Bots aren’t hard-coded and can notice the newest features in the app.

5 significant ways it is changing this dynamic:

1- Testing is becoming error-free & simple- Because the new algorithms are such significant analyzing tools, the adept software developers will no longer have to write all the scripts and examine so many data. The newest AI will also have the capability to sort through log files to improve accuracy in the specific program and to save the precious amount of time. The data results generated give developers a thorough view of the changes that must be re-enforced. It shows developers where testing is required by locating flaws in a system. Moreover, the new algorithms can also foretell future complications, which heighten efficiency during test periods.

2- Optimizing the Test Suite- One of the important flaws facing software development and testing is over-engineering those results in loss of resources, effort and time. As companies release speedy and use automation to move forth, they often struggle with huge amounts of a backlog. BOTS can also help clear the backlog and enable focus on the tests right. BOTs can identify the same/redundant and unique test cases, thus removing the duplicates and intensifying traceability.

3- Defect analysis- The intelligent approach to identify imperfection early and provide suggestions to avoid this flaw and speed up cycle time. Artificial Intelligence can accurately discover usage and failure trends to spot the most critical and less obvious faults, which allows teams to prioritize regression test cases based on dangers identified.

4- AI can eliminate extra bugs- Bugs will speedily ruin the user experience, and software test is required to halt such flaws and disruptions. When bugs are captured and caught, expert testers are left wondering how the bug went undiscovered and when the bug entered the program. With the proper use of AI the questions of when, how, and where bugs entered a system are put to rest. Testers can use the information generated by it to detect if more coding modifications will be required to control bugs from entering the program. AI is constantly testing to clear-out excessive bugs from programs.

5- Prescriptive and Predictive Analytics- BOTS thrive on data and luckily most enterprises have immense amounts of production and test data bring forth by automation suites. Artificial Intelligence can be utilized to analyze test results, identify flaws and predict the quality. It uses this data to foretell the key parameters of procedures and prescribe the best course of actions. The smart approach to detect usage and failure trends to spot the crucial, critical and less obvious faults.

AI has a world-shaking high impact on the quality function with benefits ranging from superior quality to speed to market, optimization, better coverage, traceability, and extraordinary savings on the overall cost of development.