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Future of Test Management tools

Deepak Parmar
September 16, 2021
Banner Future of Test Management Tools

Artificial Intelligence (AI) is becoming a key disrupter across many industries, and software testing is not an exception. Over the last few years, the technology landscape has evolved largely, and the IT landscape grew more complex. The customer expectations evolved too, and to meet the constant demand, businesses are constantly coming up with innovative and intuitive solutions. Along with adopting the DevOps mindset, businesses are focusing more on embracing AI and ML technologies to maximize the efficiencies of test management tools. This has facilitated delivery with faster results and complete precision. In the coming days, Agile teams that want to achieve 100% from their DevOps approaches will need to embrace intuitive test management solutions powered by different AI-enabled technologies. And when they do so, it will be a complete game-changer.

The recently released World Quality Report (WQR) 2020-2021 states that 75% of organizations will use intelligent QA dashboards powered by AI. The report also adds that 80% of respondents will generate test environments and test data and conduct more AI trials.

The role of AI and ML is going to be immense. And so, it doesn’t come as a surprise to see Digital Enterprises are investing heavily in AI-driven technologies. The AI BOTs used in test management tools can help you achieve better results in testing since they can differentiate between unique and redundant test instances, remove duplicates, and improve traceability.

Trends to watch out

Predictive and Prescriptive analysis

Predictive analytics, as the name suggests, give you suggestions based on analytics. It is powered by AI, ML, statistical data mining, and modelling to make predictions. Predictive analytics can play an important role in testing. It can predict how we are applying AI on testing. When applied, it will focus on the results of test execution. Based on the learnings, it will predict success or failure of test project, it will highlight if the test coverage is adequate or not, create error buckets, and provide visibility on measures that reduce failures. On the other hand, prescriptive analytics collects data from different predictive sources and helps in decision-making. Test management tools having predictive and prescriptive analysis integrated in the reporting feature can help testers define their test cases. This can minimize the total time and increase speed, efficiency, and quality.

Reusable framework for test assets

Certain elements of testing remain the same across different solutions. So, building reusable QA assets make a lot of sense that can help you reduce the testing time and preparation time. You can introduce reusable assets at different levels of testing. Test management tools that offer reuse tests assets and eliminate duplication, cross-project sharing of hierarchical test parameters, test data, and shared steps are going to the future of test management tools.

AI and ML to optimize testing

AI and ML can optimize the entire testing cycle. It not only offers a deep, intelligent what-if analysis, but it can help with predictions and prescription analysis so that you can tweak your test cases accordingly. AI and ML can also help to generate and manage test data. For example, you can use it to discover the gaps in test coverage compared to real-world scenarios. Modern test management tools powered by AI can help you optimize the testing by checking and removing duplicate test cases. Like, the QMetry Digital Quality Platform utilizes AI to identify duplicate test assets.

End to end Quality Platform

There is a need for a platform that offers end to end continuous testing experience and enables testing in DevOps. Such platform may offer scalable solution to manage enterprise’s scalable testing needs with modular approach.

It should offer centralized test projects management, AI enabled test authoring, test automation, key integrations with project management tools like Jira, CI/CD integrations with tools like Jenkins or Bamboo, and actionable insights driven by AI.

Key Takeaway

To increase the productivity of their testing teams and maximise their testing capabilities, DevOps teams need to choose intuitive test management tools that are backed by AI, ML, intelligent data and analytics. While there are still a limited options available in the category, AI enabled QMetry Digital Quality Platform is a comprehensive AI enabled test management tool that can be simply plugged in and played.

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