When it comes to the software quality testing process, many techniques are implemented to help to ensure potential flaws in programming can be identified from the outset and resolved before your software gets into the hands of real-life users.
When we talk about artificial intelligence, it may conjure images of supercomputers and robotics, but it’s something that will have applications in future in how we tackle many areas in life, and software testing is no different.
As the impact of digital technologies transforms our lives more and more day by day, the software we’re producing is becoming more complex and far-reaching, as well as swelling in quantity, which means that the challenge of software testing also increases. This means that the industry is continually looking for faster, more efficient ways to test software and artificial intelligence plays a key part of this, says this article from DevOps.
AI is far from a science fiction fantasy in the modern world, and its already taking effect within the industry, in a few key forms.
First up, artificial intelligence is being used to automatically generate test scripts that puts software through its paces. It’s estimated that from organisations that have employed AI testing, 80 per cent have been able to auto-generate 80 per cent of test cases reliably,
creating scripts for simple tasks such as clicking buttons, filling forms, logging in and out, for example. Tests rebuild when an element within the software is changed, ensuring the testing process is maintained also. Of course, this leaves room for 20 per cent of scripts that aren’t generated successfully by AI, but reducing the amount of work for human testers for more complex test cases.
AI is also capable of test optimisation itself. This can help find which tests are most efficient and accurate, and reduces the production of redundant test cases. Software testing can be an expensive process, so ensuring the right tests are carried out is a key element, which can be speeded up with the help of artificial intelligence.
Tests for the impact of changes on business via customers is also a key way that AI is being utilised. This will help identify any issues caused to the customer by updates and new releases, and allow quick changes before customers are driven away from the software or awaiting customer feedback. It can even be predicted ahead of a release as to whether customer satisfaction will go up or down with a new release of the software. This gives you the opportunity to fine tune software ahead of a new release, to ensure customers are retained.
This may be how AI is shaping software testing right now, but there is plenty more to come. More complex methodology which tests interconnected tech, like the Internet of Things devices, will be transformed by AI, that will also factor in whether the end user believes that the result is correct. Likewise, AI that looks into how separate personas interact with tech and software is set to come to the forefront, allowing products to be aimed at more specific target audiences.
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