Emerging trends in Testing RPA, Big Data, AI & ML

Emerging trends in Testing RPA, Big Data, AI & ML

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Introduction

Software testing is a phase of the Software Development Life Cycle (SDLC) and it is a process used to identify the precision, integrity and quality of developed computer software service/ product. It is a systematic process carried out with the aim of identifying mistakes or bugs in code so that it could be rectified before the product release to get a perfectly working product/ service to give the user a smooth experience. Testing is important because an error or a bug can turn out costly.

Software testing plays a major role in evolving software development methodologies like Agile and DevOps. The latest trend leans towards automation, Artificial intelligence with Machine Learning and SDETs (Software Development Engineers in Test) in software testing.

In this blog, we try to explain some of the latest software testing trends in the market.

Trends to look out for in Software Testing

  1. The Future belongs to Open-Source Tools:

Nowadays open source adoption is a crucial part of software testing trends. Many Service providers are rolling out flexible pricing plans which enable engineers to manage their cloud capacity with respect to their testing requirements. This in turn will enable the organizations to adopt open-source tools for proper implementation of Agile, DevOps, and Test Automation. It can be altered easily to fit with the testing department’s particular requirements. This easily editable code results in smoother functionality. Also, test cycles with open-source tools tend to be shorter than that of traditional tools. Some of the familiar open source testing tools are listed below 

  • Selenium
  • Katalon Studio
  • Robotium
  • Selendroid
  • Apium
  1. The demand of Software Development Engineers in Test (SDETs) in software testing

An SDET, is a developer who will be working in a testing team instead of a product development team. This means, SDETs are responsible not only for writing a code but for testing as well. They are required to write code, test, and fix the written code. Their roles and responsibilities vary based on the Agile lifecycle model. The Software Development Engineers in Test are usually professionals who have strong technical, and problem-solving skills. This essentially means the role of ordinary software test engineers is evolving to that of SDETs and a tester should be an SDET to survive in the industry.

Organisation’s viewpoint

Almost all software products now need out and out Test automation especially in functional, performance, and security testing. SDETs, with their dual abilities in the areas of code development as well as performing tests, are a great fit in this digital age. The SDETs can help to improve the quality of the product by the source code review process.

  1. Big Data Testing: Enhancing value for Enterprises

These days internet/technology is becoming powerful day by day with data. As this technology advances, the demand for Big data applications is getting created. However, as technology advanced, both structured and unstructured data were being generated at a huge level. Nowadays, there are a lot of structured and unstructured data is created. And the primary form of testing for big data applications are Functionality testing, Performance testing, Data validation, Data process validation, Output validation etc.

Benefits of Big Data Testing:

  • Data Accuracy
  • Data Security and Authenticity
  • Effective Decision Making
  • Right data at the right time
  • Profit boosts
  1. Test Automation in Agile and DevOps

  Test automation is going mainstream when the adoption rate of automated testing will climb to the new level, by adopting Agile and DevOps practices. Test automation supports teams in performing repeated tasks, providing continuous feedback, detecting bugs faster and more precisely. As a result, organizations can save an expansive amount of costs, time, and human resources if they integrate automated testing in their QA processes.

The popularity of test automation is increasing among enterprises with the latest agile and DevOps processes. Test automation has already climbed into the industry in testing tasks efficiently. Test automation tools continue to lead the software testing space with the proper collaboration between teams through DevOps. The best usage of automation tools helps to gain a faster release cycle and a high-quality product.

  1.  Artificial Intelligence & Machine Learning (AI & ML) in Test Automation

In software testing, machine learning is making a strong base, With the digital transformation of all major industries. With shorter release cycles, companies are demanding greater speed and accuracy from manual testers. To keep up the pace and efficiency of the process, manual testers are making use of ML like any other industry. This not only helps manual testers but also helps other testers and engineers on their team to produce higher quality work in a shorter amount of time.

With AI, the testing tools can even figure out how to recognize the controls while scanning and executing the execution cycle, independent of colour, text arrangement, size, and so on. 

Applications of AI and ML in software testing:

  • Create and automating test suites: AI and ML can help to update existing testing suites.
  • Increasing of test coverage: The advanced technology in software testing and data science will assist QA in building a requirement traceability matrix
  • Bug tracking: AI and ML can improve the exactness of error identification and tracking.
  1. RPA Testing is Even Bigger than Automation Testing

Robotic Process Automation (RPA) is the use of software with AI and ML capabilities to handle high volume tasks that previously required human effort. These tasks may be making inquiries, calculations, Record maintenance etc. RPA is not an actual robot. It does not have a physical form and no resemblance to humans But, there are different softwares (Mentioned below) available in the market which will help you to configure automation workflows.

So, Robotic Process Automation (RPA) is a business automation technology that helps in automating tasks without human intervention. This can be done in testing as well with the integration of all the testing tools using RPA. RPA helps to reduce human effort in routine repeating tasks thereby optimizing the process and the entire system.

The working of RPA includes 4 crucial phases, that is the planning phase, Development phase, Deployment and testing phase, Support and maintenance phase. Some of the popular RPA tools in markets are UiPath, Blueprism, Automation Anywhere, WorkFusion, PEGA, Redwood etc.

Advantages for organizations by RPA are,

  1. Automate routine manual testing tasks which are:  Time-consuming & rules-based 
  2. Minimum utilization of IT resources
  3.  Easier software migration
  4. Does Not require an IT infrastructure 
  5.  Cost effective and Maintaining compliance
  6. Better record collection

Conclusion

Manual testing is slowly being replaced by automated testing, leveraging enormous open source and paid tools. In order to survive in the industry manual testers need to update their knowledge in a continuous manner. Hence it will be possible to see an almost complete replacement of manual testing with automatic testing. At the end, testing is no less important than the development itself. It is triggered by shortening terms, increasing requirements and the frequency of changes to the software code. Thus, the main trend in the upcoming years is the increasing role of the “testing department”. Companies that do not do the test a full-fledged part of their strategy will fail.

For more information  on the topic go to Innovature’s Security testing  page

 

Vishnu Suresh

Experienced Software Test Engineer of Innovature by managing and monitoring all installed systems and infrastructure. Installing, configuring, testing and maintaining operating systems, application software and system management tools.

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