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What’s Next in the world of Automation?

“Opportunity does not waste time with those who are unprepared.” ― Idowu Koyenikan


While keeping that in mind, I’ll be discussing the possible future shifts that might take effect in the field of automation testing in the present blog.


What’s next?

Of course, this big question always hovers around our minds and the answer to that is the future is bright in the field of automation if you are prepared for it. According to the World Quality Report (Capgemini), the importance of quality assurance has taken the industry by storm with a great emphasis on the value of testing. The onward march towards digitization emphasizes and ensures that the quality of the product provides a seamless customer experience.

In the past few years the focus has shifted from Functional testing to Automation testing, and going forward companies are adopting the model of low code testing/ codeless testing to bring more efficiency in delivering a great value product. This is also referred to as digitization sometimes. In addition to this enterprises are looking to make their automation model more effective by incorporating cloud testing, Artificial Intelligence, Machine Learning, Robotic Process Automation, and natural language processing (NLP).


Way forward

The next steps would be to move forward with the changing technology and adapt to business needs. I’ll be summarizing about few technologies to look out for in the year 2023 and get well-versed with these.

1. Cloud Based Testing

2. Continuous Testing (CI/CD)

3. Script less/ codeless Automation Testing

4. AI/ML Testing

5. Microservices Testing


1. Cloud Based Testing:

Cloud-based software testing is used to assess web applications for scalability, performance, security, and reliability. With the utilization of Cloud service models, enterprises can implement testing as a service, without the need to completely invest in testing labs, tools, or infrastructure. The cloud testing market is expected to register a Compound Annual Growth Rate (CAGR) of over 13% over the forecast period (2021 - 2026). The demand for cloud testing is increasing owing to the capabilities of cloud sourcing technology in software testing activities to perform quality assurance (QA) and remove bugs.



This Picture depicts the increase in the annual growth rate from 2023 to 2028.

Benefits of cloud-based Testing:

  • Cloud based testing is cost-effective, because it enables IT and software developers to initialize practical experimental tests on cloud platforms without the necessity to possess licenses or purchasing the resource.

  • The Pay per use policy of cloud services is the most notable factor for enterprises, where companies have to only pay for the service based on the utilization time and can stop leveraging cloud services once the testing is complete.

  • Automation achieved using cloud-based testing automation tools aid in improving collaboration between diverse teams and members of the same team which is useful in avoiding any ‘activity overlap’ between team members.

  • When collaborating in the cloud-based environment, developers and testers can connect in real-time, work more efficiently, and give feedback faster.

Tools to implement cloud based testing: Some of the tools that can be used to implement cloud based testing are Amazon Web Services, BugBug, BlazeMeter.


2. Continuous Testing (CI/CD)

Continuous testing (CT) is a software development process where applications are tested continuously throughout the entire software development life cycle (SDLC). The continuous testing market is estimated to grow from USD 1.15 billion in 2018 to 2.41 billion by 2023. This represents an annual growth of around 16%. Depicting the need for the timely delivery of high-quality software. The goal of continuous testing is to evaluate the quality of the software as part of a continuous delivery process, by testing early and often.

Benefits of CI/CD:

  • CI/ CD testing removes the roadblocks that can happen when performing testing in a single step.

  • CI/ CD testing directly supports DevOps and the goal of delivering high-quality software, faster as the code is tested automatically as soon as it gets integrated.

  • It provides a better customer experience as it ensures better quality and performance of the product.

  • Provides a collaborative relationship between the QA, Dev, and Operations Team

Tools to implement CI/CD: Jenkins, Bitbucket, Buddy, Bamboo.


3. Script less/ codeless Automation Testing

Scriptless test automation is an approach where users can automate test cases even if they lack in-depth knowledge of the code. Scriptless Test Automation is the system in which all the frameworks, codes, libraries, and test cases are directly included in the backend. According to future market insights, the demand for codeless testing will rise at 15.5% CAGR between 2021 and 2031 in comparison to the 10.6% CAGR registered between 2016-2020. The factors responsible for the rapid growth of codeless testing tools include the easy evaluation of code by non-technical team members and the reduction of time that testers spend on repetitive test cases.

Benefits of scriptless testing:

  • Reduction in the time needed to automate the tests since far less time is spent on creating the automation and writing the test code.

  • Reduction in the cost of automation.

  • It provides the flexibility of reusing test cases in different scenarios.


Tools to implement scriptless testing: Selenium IDE is an open-source platform for implementing scriptless testing. In addition to Selenium IDE, TestCraft, Katalon Studio, Testim and Cloud QA are a few among others.


4. AI/ML Testing

The global market of AI was just $1.4 billion in the year 2016, It is said that the global market of AI is expected to be almost $60 billion by 2025. These numbers depict the inevitable indulgence of AI in the field of testing and almost everywhere. Artificial Intelligence and Machine Learning use predictive models to identify the different features for testing and prepare specific test plans without any human support. A large amount of data can be analyzed, test cases can be reused, and detailed test reports can be generated with the help of AI and ML.

Natural language processing (NLP) is an artificial intelligence specialty by which machines can identify, interpret, and generate human language. The aim of NLP is to build machines that can approximate human language comprehension.

Brief overview of How NLP works:

During the implementation of NLP, the Functionize NLP engine ingests human-readable, preformatted test cases. These test cases can be written as simply and naturally in Microsoft Word or Excel documents. Many such statements can be easily combined and fed into the Functionize NLP engine, which rapidly and intelligently processes the entire set of test cases—and generates each of the steps for the test case.

Limitations of NLP:

There are some limitations of NLP based testing which include the inaccuracy of test results due to a lack of necessary information and, maintaining the same writing style during the creation of test scenarios.

Benefits of AI/ML based testing:

  • Generation of accurate test cases with almost 100% test coverage.

  • Reduced time in the creation of test cases.

  • Increase the productivity and reusability of the tests.

  • It helps analyze the company’s product with respect to all aspects of development.


Tools to implement AI/ML: Amazon Comprehend, Google cloud NLP API, Testim, Mabl and AppliTools


5. Microservices Testing

Microservices architecture allows development teams to create a product as a suite of small autonomous services formed around a particular business domain. Microservice testing is becoming a huge part of CI/CD testing. Microservice testing is also easy to integrate with the DevOps environment which can be helpful in reducing the risk of falls in business applications.

Benefits of microservice Testing:

  • Easy to deploy.

  • Improved accuracy.

  • Helps in bringing the product to market at a faster pace.


Tools to implement microservice testing: Mocha, Jest, and Supertest.


Conclusion

With the advancement of technology in automation testing, the best way forward is to adapt to the changes and excel as we go. We can make use of all the new tools and techniques to make ourselves ahead of the industry. With that being said, I wish all the best and a happy learning journey to all the seekers.

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