The importance of intelligent test automation
Digital transformation has disrupted time to market like never before. Reducing the cycle time for releasing multiple application versions through the adoption of Agile and DevOps principles has become the prime factor for providing a competitive edge. However, assuring quality across application releases is now proving to be an elusive goal in the absence of the right amount of test automation. Hence it is no surprise that according to the Data Bridge Market research, the automation testing market will reach an estimated value of USD 19.9 billion by 2028 and grow at a CAGR of 14.89% in the forecast period of 2021 to 2028.
Test automation is a challenge, not only because an organization’s capabilities have traditionally been focused on manual testing techniques but also because it’s viewed to be a complex siloed activity. Automation engineers are expected to cohesively bind the vision of the business team, functional flows that the testers use, along their own core component of automation principles and practices. Production continuum can only become a reality when there is a disruption to automation as a siloed activity, ably supported by maximum collaboration and convergence of skillsets. Even then, without the adoption of the right test automation techniques, it becomes near impossible to realize the complete value.
Outlined below are steps towards making test automation initiatives more effective and results-oriented.
Comprehensive coverage of test scenarios
Test automation, to a large extent, focuses on the lower part of the test pyramid addressing viz – unit testing and component testing but neglecting the most crucial aspect of testing business-related areas. The key to assuring application quality is to identify those scenarios that are business relevant and automate them for maximum test coverage. The need of the hour is to adopt tools and platforms that cover the entire test pyramid and not restrict it to any level.
Read more: The right testing strategies for AI/ML applications
A test design-led automation approach can help in ensuring maximum coverage of test scenarios. However, given that this is a complex area, aggravated by the application complexity itself, what tools can help with is to handle the sequence of test scenarios, expressing the business rules and associating data-driven decision tables attached to the workflow, thereby providing complete coverage of all high-risk business cases. By adopting this sequence, complexity can be better managed, modifications can be applied much faster, and tests can be structured to be more automation friendly.
This approach helps to analyze functional parameters of the test in a better way and helps to define what needs to be tested with sharp focus, i.e., enable a sharper prioritization of the test area. It aggregates various steps involved in test flow along with the conditions each step can have and prioritizes the generation of steps along with risk association.
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Sharp focus on test design
The adoption of Test Driven Development (TDD) and Behavior Driven Development (BDD) techniques aims to accelerate the design phase in Agile engagements. However, these techniques come at the cost of incomplete test coverage and test suite maintenance-related issues. Test design automation aims to overcome these challenges by concentrating on areas like requirements engineering, automated test case generation, migration, and optimization. Automation focus at the test design stage contributes to tremendous value-add downstream by removing the substantial load from scripting test cases and generating them.
Adoption of the right toolsets accelerates the inclusion of test design automation during the earlier stages of the development process, making it key to Agile engagements. Most test design automation tools adopt visual-based testing. They make use of graphical workflows that can be understood by all project stakeholders – testers, business stakeholders, technical experts, etc. Such workflows can be synchronized with any requirements management toolsets and collaboratively improved with inputs from all stakeholders. User stories and acceptance criteria are contextualized so that everyone can see the functional dependency between the previous user stories and the ones that were developed during the current sprint.
Collaboration is key
Collaboration is the pillar of Agile development processes. By bringing collaboration into test design, risk-based coverage of test cases can be effectively addressed, along with the generation of automated scripts on a faster note. Automation techniques steeped in collaboration provide the ability to organize tests by business flows, keywords, impact and ensure depth of test coverage by leveraging the right test data.
By integrating test automation tools into Agile testing cycles, a collaborative test design can be delivered with ease. With such tools, any changes to user stories can be well reflected; users can comment on the flows or data, identify and flag risks much earlier. These tools also enable the integration of test cases into test management tools of choice like Jira and generate automation scripts that can work under different automation tools like selenium.
Making legacy work
Most organizations suffer from a huge backlog of legacy cases – there is a repository of manual test cases that are critical for business. Organizations need them to be a part of the agile stream. For this to happen, automation is mandatory. Manual test cases of legacy applications are very rich in application functionality and make good sense to get retrofitted into test automation platforms.
New age test design automation frameworks and platforms can address legacy tests that are already documented, parse them, and incorporate them as a part of the automation test suite. Many of these tools leverage AI to retro engineer manual test cases into the software platform – graphical workflow, test data, and test cases themselves can be added to the tool.
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A closer look at the current test automation landscape outlines a shift from the siloed model that existed earlier. Clearly visible is the move towards automation skillsets, coding practices, and tools-related expertise. Automation tools are also seen moving up the maturity curve to optimize the effort of test automation engineers, at the same time enabling functional testers with minimal exposure to automation stacks to contribute significantly to automation effort. All in all, such shifts are accelerating the move towards providing organizations the ability to do more automation with existing resources.
Trigent’s partnership with Smartesting allows us to leverage test design automation by Integrating these tools in your Agile testing cycles, thus being able to quickly deliver collaborative test design, risk-based coverage of test cases, and faster generation of automated scripts. We help you organize tests by business flows, keywords, risks, depth of coverage, leveraging the right test data, as well as generate and integrate test cases into test management tools of your choice (JIRA, Zephy, Test Rail, etc.).
Our services will enable you to take on your documented legacy tests, parse them and bring them into such tools very quickly. Further, we help you generate test automation scripts that can work under different automation tools like Selenium & Cypress. Our services are delivered in an As-A-Service Model, or you can leverage our support to implement the tools and the training of your teams to achieve their goals.
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