Big data plays a vital role in many business sectors including healthcare, telecom, retail, banking, technology, media and so on. Enterprises across all the industries regularly deal with diverse data types and huge data volumes. It helps in enhancing market strategizing and makes better decisions with precise data validations. Big data testing is not a new phenomenon but is expected to grow aggressively as the industries are shifting towards a data-oriented world. According to the Mordor Intelligence report, the technology and service market for big data will grow from $23.1 billion dollars in 2018 to $79.5 billion dollars in 2024.

The tendency towards big data testing is widely adopted because the enterprises are following a strong process that forms most of their marketing strategies. It can be said that the volume of data today is enormous, and more the data, the more time is needed to carry out the test and more resources will be needed for quality testing. That is why it is easy to see that big data testing services will only become more and more popular in the future.



You are familiar with the term “DevOps” which is a set of software development practices that associates development and information technology operations. The main aim of DevOps is to compress the systems development life cycle so that the teams can focus on fixing bugs, building features and frequent updates that are aligned with business objectives. As DevOps collaborates developers and business operationalists, with the same spirit, QAOps increases the direct flow of communication between testing engineers and developers by merging software quality assurance testing into the CI/CD pipeline, rather than having the QA testing services team to operate in isolation.


To put the concept of QAOps into action following high-level testing practices are used –

  • AUTOMATED TESTING – Automation testing is one of the main pillars of the QAOps framework and includes performing tests with the help of technology and minimal human effort. Before building the automation framework, QA engineers should study the product in detail and understand the specifications. The type of testing that is automated the most is the regression test cases which require a thorough phase of planning and documentation for automation testing.
  • PARALLEL TESTING – In the QAOps framework, testing should run promptly in parallel with the delivery pipeline. The delivery process will be directly affected if the testing efforts are slowed down. It is essential for the testing engineers to run multiple tests at once instead of running them one after the other because even the automated tests will not speed up the testing process if they are executed in a serial manner.
  • SCALABILITY TESTING – Scalability testing helps QA engineers to uncover the challenges related to the performance of web applications. After every release cycle, the web application continues to scale and with this the testing requirement also scales. The routine of testing should be scalable with the CI/CD pipeline which scales up and down with the requirements of the project. In order to increase the speed of tests when needed, the QA teams should have the scalable infrastructure to perform the testing.
  • INTEGRATING DEV AND IT OPS IN QA – The final practice in the QAOps framework is to make the QA activities a part of the CI/CD pipeline. The easiest way to integrate development and IT operations with QA is to make the IT operation engineers identify potential UI/UX problems with the web application with the assistance of the QA team and make developers write the test cases. This will make a clear picture of the complete QA process for developers and QA engineers after they collaborate.

QAOps can be flexibly scaled up or down to fit any size of business and can be applied to giant tech companies, medium and small businesses. As the enterprises are gearing towards DevOps, we can expect to see QAOps as a spreading trend in 2020.


As per a leading research analyst, artificial intelligence is present everywhere and in all spheres of technological innovations. It will be the top priority for investment in 2020. In North America alone, the market for AI is expected to be around $6-7 billion. We can expect the applications of AI in more testing areas like log analytics, test suite optimization, ensure test requirements coverage, predictive analytics, and defect analytics.

Another pillar is Machine Learning which is expected to grow on another level in 2020. The outlook of technology has literally been changed with machine learning due to the prediction of various tasks based on complex neural networks and algorithms, these applications also need continuous testing and validations.


By IoT Testing we mean testing the IoT devices for security assurance, trustworthiness, compatibility of device protocols and versions, ease of use, monitoring the delay in connection, evaluation of data integrity, device authenticity, the versatility of programming items, so on and so forth. The QA teams should expand their knowledge and enhance their skill for performing IoT testing as the IoT testing engineers face an extensive amount of work in this area especially with operating systems and monitoring communication protocols.

In order to enable efficient and well-connected smart devices, enterprises have already started identifying the need for an effective IoT testing strategy. Testing the IoT devices was already prominent in 2019 and it is expected that the number of IoT devices all around the world will reach 20.6 billion by 2020 compared to 6.4 billion in 2016.


In Quality Assurance, test automation is no longer a foreign thing, 44% of IT organizations automated 50% of all their testing in 2019 and more adoption of automated testing will continue to be on the rise in 2020. Test automation services have become a crucial component, as more and more businesses are adopting the latest agile and DevOps processes to fulfill the demand for quality at speed. Organizations that adopt automated testing in their QA process save a significant amount of time, cost and human resources. Test automation services help the teams in performing repetitive tasks, detecting the bugs precisely and faster, ensuring coverage of the test and providing continuous feedback loops.


The top 5 test automation testing trends that shape the future of software testing industry are as follows –

  • CODELESS TEST AUTOMATION – Codeless test automation is introduced in order to increase the scalability of test automation. It facilitates the business users and software testers to automate the test cases without thinking about the coding. It decreases the time consumed to understand the code and helps to deliver faster results.
  • ARTIFICIAL INTELLIGENCE – In order to make the application reliable, the world is adapting Artificial Intelligence. Machines will gradually be taking control instead of human interference and manual testing.
  • ROBOTIC PROCESS AUTOMATION – RPA is the latest technology that possesses the competence to re-invent the business process management aspect. The transformations in the software testing and AI world have covered the path for Robotic Process Automation.
  • BLEND OF AGILE AND DEVOPS – with the digital transformation, there is the adoption of methodologies and organizational practices like DevOps and Agile. The software testers will become the quality trainers which will aid in faster deployments and assure high-quality products delivered in a cost-effective manner.
  • ADOPTION IN IOT TESTING – Most of the business enterprises today are grasping on to the Internet of Things. The performance, security, and usability of the IoT apps and devices are tested and before acquiring the product most of the customers depend on IoT testing. These technological improvements push the QA testers to enhance their skills and expertise frequently.

The process of performance engineering involves collaboration of software, hardware, performance, configuration, security, usability, business value and it delivers the highest value which exceeds the expectations of user. There was a time when product performance was the major segment of continuous testing but now it is shifting towards performance engineering which is not an easy process. The assessment of the quality of the application testing can be more accurate if it is possible to divide the test into several parts which can be done by parallel development.

The performance engineering teams need to do the following –

  • DEFINE KPIs – Developers need to define the app’s success for their business and accordingly require the teams to be meticulous with data and analyze the root cause of the performance issues.
  • MANUAL ANALYSIS – With the automated collection of data, comes the need for manual scrutiny. The developers hence should utilize their time wisely to create reproducible results when testing and altering the application software.
  • THINK OF PERFORMANCE FORM THE START – Developers should visualize the perfect performance of an application that will allow the team to set specific and clear business goals.
  • CONTINUOUS PERFORMANCE TESTING – In order to identify behavior trends, avoid performance issues and incorporating efficient design elements in the future the teams should monitor applications and the user experience.
  • MAKE CHANGES – Based on the reliable performance data, the teams should actually the application even if it is challenging to rewrite the legacy code.

There has been the emergence of various security threats with the digital revolution. The security testing of applications, networks, and systems not only ensures secure transactions but also completes the protection of end-users critical data and the CIOs of the enterprises are realizing its importance now. Thus, we can say that security testing has gained a lot of importance and is on the rise for 2020 as it prevents economic losses and safeguards brand loyalty.


Quality Assurance Testing, like any other development element, is rising to a new level and experiencing a lot of changes. The traction is towards the new software testing trends stated above and no matter how the digital transformation will turn in 2020, it is certain that the testing engineers will have to witness adjustments and changes. A huge amount of attention will be paid to artificial intelligence and manual testing will be gradually replaced by test automation services. The enterprises need to stay updated with the latest QA testing services trends in order to ensure quality products.

Webdunia has spent more than 20 years assisting enterprises to address their quality assurance and testing needs leveraging manual and automation testing methodologies.

Webdunia’s software and infrastructure testing services fit every stage of technology lifecycle – be it the development of a solution from its core, managing existing digital assets or upgrading existing technology infrastructure and applications to a superior platform.

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