Software Testing in the Realm of AI, IoT, and Robotics
Experience Faster Development, Testing, and Deployments with AI and ML Testing, Internet of Things Testing, and QA BOTS.
Emerging technologies are here, and Businesses are rapidly embracing them to get any competitive advantage and differentiation they can get. Digital transformation is impossible without the adoption of new and emerging technologies. This is causing major technological disruptions that businesses must learn to cope with. Whether its Big Data, AI, Machine Learning or Robotics, companies need confidence that these emerging technologies will function correctly and deliver the expected benefits.
QA and testing has become even more critical. The efficiency of AI bots needs to be tested, Big Data testing is required to ensure data completeness and confirm the quality of data.
We advise and help companies with their emerging technology initiatives through rigorous performance testing, functional testing, and security testing, and validations under different conditions.
AI-Based Testing (QA BOTS)Extend AI to Testing to make QA Intelligent
Improving Technology with Automated QA Tools. AI and Bots have revolutionized Software Testing and development in terms of testing scope and workloads, debugging adequacy, and advanced continuous testing. As companies evaluate AI testing to support their Digital Transformation initiatives, they need a QA partner with the right experience & skills to guide them by taking a holistic approach to optimizing the entire testing lifecycle.Typical challenges companies will face include:
- Prioritizing, clarifying, gathering test requirements
- Identifying relevant and suitable test cases
- A lack of expertise with the latest AI technologies and tools
- High test script maintenance cost considerations
- AI and NLP based Continuous testing, by executing relevant automated test cases per commit from the Regression Test repository
- Optimize existing Test Suite by removing redundancies which in turns increase Test Coverage
- Identify High failure module by analyzing defects using AI
- Faster and More Stable UI Tests using AI-based tools such as Applitools, Sauce Labs, Testim, and ReTest
- Mimic and validate Partner EDI Transactions with our Robotic Process Automation based QA Bots
- Automated Regression, Smoke and Sanity Test suite using QA Bots
- Fast and Simplified Automated Testing for Chatbots
- Simplified Automation Maintenance
- Business Process Testing using Workflow based QA Bots
- Code-less: No need to memorize any syntax
- Simplicity: Easy to create a process through simple drag and drop
- Scalability: It can be achieved by assigning work to multiple workstations
- Cost-saving: Huge reduction in cost as a very minimal workforce is required
- Accuracy: As the tasks are performed by the Bots
- Productivity: As it is robotic, productivity will be very high
- Flexibility: The test process does not depend on the type of software under test, whether it is web-based, desktop application, or mobile application
ML testingNextGen QA with Machine Language (ML) Driven Test Automation
Using Artificial Intelligence for testing the Quality of your enterprise ecosystem. We are witnessing a wide adoption of Machine learning (ML), in a range of areas, from Finance, Energy, and Health, to Transportation. Given this growing importance of ML-based systems in our daily life, it is becoming very vital to ensure their reliability. Typically, ML Models are developed and tested by data scientists themselves. But ideally, it should be a quality assurance team that should be performing QA by running tests as like traditional software to test the ML models from time-to-time
We provide Advisory and Implementation Services around Machine Learning Testing, we adapt concepts from the software testing domain (e.g., code coverage, mutation testing, or property-based testing) to help ML engineers detect and correct faults in ML programs.Our Machine Learning Models Black box Testing Approach consists of:
- Testing performance of ML Models
- Testing the relationship between each feature and the target
- Target Test Data set which triggers testing of all features
- AI-Based Test automation using tools like Testim.io, Functionalize, etc.
- Improve Overall test coverage
- Improve Model performance
- Test suite optimization
- Log Analytics
- Defect analytics
- Rapid impact analysis
- Comprehensive documentation
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