Atalgo Computing is a specialist technology consulting with experience in enterprise test automation. By virtue of seeing up close and being part of various product engineering and quality engineering initiatives, we have developed decent competency in test automation and overall DevOps based automations. Test automation field is changing fast and there is an expectation from technical delivery as well as business to be more innovative and bold in terms of the solutions we provide. As of 2021, there are few clear trends for test automation field which I am outlining below.
Coverage/Breadth
Traditionally, test automation has been more focused on UI based workflow automation mostly useful in Smoke and Regression testing. We have felt the need to increase the coverage of the test beyond regression testing and move more towards exploratory testing with expanded coverage. Also, test automation should cater for unit testing, integration testing, security testing and performance. Also, closer to the browser actions kind of architecture allows automation engineers simulate the behavior of the application more efficiently (for example, we shouldn’t need to insert explicit wait command in the script but rather test script should automatically wait for the next command). This is one of the reasons Cypress is gaining more traction as compared to Selenium.
Debugging
As test automation is becoming more prevalent in IT projects, developers and testers are trying to leverage as much automation as possible; across the different test phases. This generates need for test tools to provide better debugging, ability to integrate with IDEs and add break points to save time while developing test scripts. We will see more tools capable of providing better error analysis, debugging and analytics from quality engineering perspective. These are the few improvements we see in Cypress based/inspired test automation tools over traditional ones.
Continuous Testing
Continuous Testing is about testing as part of DevOps pipeline in an automated fashion. This provides better and early control over the quality of the code as bugs can be caught at Build/Unit Testing or Deployment phase without much involvement from testing team once infrastructure is in place. Continuous Testing is gaining lot of traction in DevOps mature organizations. Although, we have seen test frameworks effectively integrated with CICD pipeline however, I feel more needs to be done to leverage the analytics coming from the wealth of data on CICD and Continuous Testing activities. A better and holistic analytics approach will be able to drive more value from the Continuous Testing pipeline and help design more targeted test suite for subsequent releases.
Microservices
Microservice architecture provides unparalleled flexibility in application development. This has also thrown new challenges in testing microservice based applications. This testing approach is API driven and mostly “shift left”. We need to ensure that when APIs communicate with each other, their communication conforms to the API contracts. Many specialist contract testing tools such as Pact are emerging in the market and I expect this space to be buzzing with activity.
AI Augmented Solutions
AI/ML based techniques and toolsets are going to provide paradigm shift in test automation space. As current toolsets with integrated work flow management and CICD pipelines capture more and more data, we will be able to leverage AI/ML methods to drive test automation intelligently. Codeless scripting, Natural Language Processing (NLP) based script development, Self Healing, Smart Analytics are few of the AI use cases in test automation. We also expect to see role of AI/ML in test scoping and defect analysis. Visual automated validation is another area where AI can play a significant role in testing the responsiveness, look and feel of the software without involving manual testers. AI will play a big role in maintaining test scripts efficiently in near future.
What Are We Doing
We at Atalgo are developing an enterprise grade test automation platform, Flame. Flame is a modern AI augmented test automation platform which caters for most of the automation needs discussed above. We support Web, Mobile and API testing from the single platform and provide AI augmented self healing capabilities. As of April 2021, tool is under beta testing with the aim of a commercial launch by July, 2021.
Intriguing read!