Testing is changing.
Automated software testing has boosted efficiency in major businesses, reduced time to market, and positively impacted the quality of delivered product for companies who’ve embraced it. But automation was just the beginning. Now there’s another step to take: Artificial Intelligence (AI).
Integrating the power and flexibility of AI into automated testing accelerates the process, further improving delivered product. Choosing not to implement AI – in a market where competitors are almost certainly finding an edge in doing so – means a real risk of falling behind or even becoming obsolete.
Software systems are escalating in complexity. Data volumes are increasing exponentially. Software needs to be developed in a way which cleverly accommodates future demands. These things all mean that AI will one day not be an enhancement, but a necessity in automated testing.
What is Artificial Intelligence?
AI covers a very broad range of concepts. It reaches all the way from simple reactionary systems – possible in a few lines of code – to full-fledged and hugely complex examples like driverless cars. As a general definition, an AI system will exhibit any number of behaviours that we consider intelligent. These typically include the capacity to learn, adapt to new situations, and make optimal decisions.
While there are futuristic views of AI, which present it as a self-aware entity that will render the human element obsolete, these are rather far from fruition. The pragmatic direction in which AI is developed, is as yet another tool which increases the ability, speed, accuracy and overall efficiency of the human process – A new generation of intelligent tools complements human intelligence, and makes our technology more flexible.
Many business sectors have already applied AI to their major processes to great effect. A good example is Amazon, which has completely rebuilt its business around AI systems. Some of these are the product in themselves – the Alexa assistant, for instance – while others power a back end which sells more, reduces errors, and works more efficiently. Market intelligence firm Tractica predicts that AI-influenced trading revenue will rise from $643.7 million in 2016 to $36.8 billion in 2025. AI is here, and it’s making a difference.
Machine Learning (ML) is a very promising discipline of AI which has been tried and tested in various applications within the industry, as it can be used to make predictions, detect trends and irregularities, by using statistical methods to extrapolate new information out of data, which is then used in various decision making processes.
The advancements in processing power, as well as the availability and exponential increase in the size of data, have resulted in an unprecedented increase in popularity of ML. Already a large number of data-driven companies have integrated machine learning into their business processes which can be found at the heart of retail, financial as well as social media companies.
Why test with AI?
There may be no better application for AI than in enhancing automated testing. AI-led testing can bring to light issues earlier as it analyses data as it goes – helping companies find solutions faster and reducing the burden on human testers.
Testing is never a one-time process: A set of test scenarios has to be executed at each development iteration throughout the lifecycle of any software, with the number of test scenarios increasing with each new added functionality.
Automated testing has greatly increased the effectiveness and speed of software testing, by removing the need for a human tester to repeat the exact same tests, with the added benefit of having test scenarios expressed in a consistent and formal manner. The limitations of automated testing arise from two key factors:
- The clockwork nature of automation does not always allow sufficient flexibility to accommodate software with dynamic content and features
- Test development often relies on the intuition and skill of the developer, and requires a good understanding of the System Under Test (SUT).
The introduction of artificial intelligence can greatly reduce the effort and complexity in analysis and implementation associated with software testing, as well as the quality of the tests by leveraging the ability of a tester to analyse a SUT.
Fuzzy logic is a technology that has found application in situations where the effectiveness of conventional types of logic is limited, and can be found at the core of many AI technologies. Its strong potential in testing is due to the ability of fuzzy logic to produce valuable results in problems riddled with uncertainty and ambiguity.
AI augmented software testing can result in improved test quality, faster delivery, and an end to clockwork testing. Most importantly this analytic and data-driven approach has the potential to change the nature of the automated software testing process altogether.
Things to consider
Like any process improvement, the benefits of AI have an allure that makes it tempting to jump in immediately. Not embracing AI means the potential of your business taking a back seat whilst you watch your competitors soar. There’s no doubt that it’s an essential move, but it’s one that needs to be handled with care. The way AI is applied to testing processes must be systematic and intelligent in itself.
AI cannot solve every problem. Instead, it is important to discover and analyse those problems it can solve, and to understand the requirements and impact that introducing AI into your systems will have.
Rush into implementation without proper research and consideration, and you could end up investing time and money into a solution which is not appropriate for your business. Fail to invest in the proper training and documentation, and you risk your testers losing touch or using the new technology incorrectly. For AI to improve automated testing, it needs to be fully understood.
ECS Digital’s QA team has long been working with and developing AI processes to augment automated testing. Its internal AI group have also been educating staff and promoting good development practices throughout the company.
As both AI users and consultants, ECS Digital are uniquely placed to inform our clients on the right way to implement AI in their testing processes. AI doesn’t come off the shelf – it needs to be tailor made to suit you.
ECS Digital have the expertise and experience to advise exactly how integrating AI and automation can help your business and can recommend the solution that best fits your needs.
Get in touch to discuss how you can revolutionise your testing process.