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As Agile and DevOps go main stream, with emphasis on CI/CD, AI and machine learning, businesses can adopt automation by letting the tester automate the repetitive parts. A lot of effort and time is invested on research in AI and machine learning to help speed up testing and automation. Working with TechArcis will cut short the time spent on research and figuring out solutions, our experts can help you design and implement the right solution the first time and save lot of time, effort and money.
Testers can be more focused on the creative, logical and reasoning part that will be significant in the inter-connected world. At TechArcis, we have fully equipped labs with the necessary infrastructure that help clients invest in innovation and test their products using analytics, AI / Machine learning and robotics.
- Smart Testing enabled by using AI and Machine Learning to analyze data from various sources, identifying redundant test cases, classifying correlated test cases into clusters.
- AI and machine learning enabled automation by letting the tester automate the repetitive parts.
- Focus on the creative, logical and reasoning part that will be significant in the inter-connected world.
- Use of Robots for automating POS testing.
- In house Robotics lab – Continuous innovation and testing as per client requirements.
In today’s highly connected world, testing is critical and has become an extremely important activity. Yet, businesses can’t do exhaustive testing as that’s impractical due to resource and time constraints. It is here that artificial intelligence and machine learning can help spot areas that need to be tested and analyze data to identify repetitive patterns that could be automated.
TechArcis – Testing with Analytics, AI, Machine learning and Robotics
A lot of research is happening in these areas and businesses can benefit from Testing use cases such as:
- Data analysis : Using AI and Machine Learning to analyze data from various sources (server logs, defect management tools such as HP ALM and ITSM tools for log data aggregation etc) to identify applications with a history of raising defects.
- UX improvement with sentiment analysis and consumer feedback: Conduct sentiment analysis by extracting trends and analyzing data extracted from app stores (Google Play/Apple Store), social media (Facebook/ Twitter), and from consumer web sites (such as a retailer). Such analysis can help identify issues which can then be addressed through performance testing and usability testing.
- Test case optimization: From identifying redundant test cases to classifying correlated test cases into clusters and executing a few test cases (that are not identical but share similarities and have the same test fail/pass patterns), test execution effort can be reduced significantly.
- Defect prediction for Agile: Using historical data of test cases pass/fail performance for one given sprint to predict a specific sprint’s test pass/fail can help reduce test workload by avoiding testing what doesn’t need to be tested. As Agile and DevOps go main stream with emphasis on CI/CD, AI and machine learning will help automation by letting the tester automate the repetitive parts with more focus directed on the creative, logical and reasoning part that will be significant in the inter-connected world.
- Robotic Testing: From using robots (that can write signatures on a touchscreen, press buttons, hold and swipe multiple cards within a stipulated time) for automating POS testing, to using them for testing handheld control devices and for unattended EMV testing (where they enter cards, punch the PIN code etc), AI and machine learning are helping to automate several time consuming, repetitive tasks.
“TechArcis demonstrated their passion for innovation when they took on my most challenging automation problem. TechArcis team was instrumental in providing automation approach for our EMV testing platform with help of robotics which helped automate all manual process like menu selection and pin entry”
“Director, Payments Industry”
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Watch the Video Role of QA and Testing in Digital Transformation Journey