Artificial Intelligence-led Testing
While leveraging AI for testing apps for quality, enterprises may face multiple challenges such as identifying the exact use cases, lack of awareness about what really needs to be done, verifying the app behavior based on the data that has been input, testing apps for functionality, performance, scalability, security, & more. Avani’s extensive experience in the use of AI, ML, & analytics helps enterprises improve their automation frameworks & QA practices. Avani provides AI/ML-led testing and performance engineering services for your QA framework through implementation of its next gen IP, BlueSwan™.
Defect Analytics
Use of AI-based Sentiment Analytics: BlueSwan Avani Enterprise Sentiment Analyzer (CESA) – AI-tool to find, categorize, and distribute the overall sentiment of a conversation (Positive, Negative, Neutral) for better decision making
Realtime Dashboard & AI-based Predictive Analytics: BlueSwan Verita™ – Analytics-driven workload modelling for defect prediction, code coverage, response time, & scalability prediction
Performance Engineering approach
ML-based analytics driven Performance Predictions: Workload modeling & response times
Regression Optimization
Automated collation of the dependent test cases/scripts-based on the changes:Avani Impact Analyzer – solution for test suite impact analysis during Change Requests, Patches, & upgrades
Automated prioritization of test cases/scripts-based on Machine learning
Smart Automation
Automated change detection in the object properties across scripts for every new release
Self-healing of test scripts based on the application changes
With a strong focus on AI algorithms for test suite optimization, defect analytics, customer sentiment analytics, scenario traceability, integrated requirements traceability matrix (RTM), rapid impact analysis, comprehensive documentation and log analytics, at Avani, we have established a 4-pronged AI-led testing approach that includes:
- Discover – Smart asset creation using data repositories including defects, tickets, logs etc. for analysis
- Learn – Identify relationships between test assets such as defects and software requirements for insights
- Sense – Predict occurrence of an incident, impact, and likelihood led by analytics and insights
- Respond – Respond to an incident, input the resolution and results for continuous learning
Avani’s AI-led DSLR Testing Approach
Avani’s AI & ML Center of Excellence
Access Avani’s AI & ML CoE that includes:
- Verita: a critical component of Avani’s next-generation IP, BlueSwan – a quality engineering platform and dashboard with predictive analytics capabilities
Prudentia: another component of BlueSwan – a model-based testing tool that automatically generates intelligent software testing procedures and scenarios using models of system requirements, leveraging a patented algorithm
Social Sentiment Analyzer Tool: an in-house tool created by the Avani Innovations and R&D team, powered by Machine Learning & AI that identifies and categorize feedback expressed by end-users to determine (both objective and subjective) their experience from a product & service quality perspective and create actionable insights. - An enhanced Avani test automation framework that supports various RPA tools for matured automation practices
- A Test Automation CoE with ML and AI-assisted tools such as Applitools, SauceLabs, Testim, Sealights, Test.AI, Mabl and ReTest
Algorithms to test your AI systems
In this era of daily deployments and DevOps transformation, organizations need to automate the test requirement traceability and versioning to accelerate the QA cycle, reduce overheads in test management, and provide superior quality governance.
Avani’s Intelligent Test Case Management Methodology offers assured benefits of:
- Faster deployments
- Matured governance over test data and test suite
- Better traceability with backward & forward integration
- Holistic approach with early feedback with unattended execution
One integrated platform
Avani’s Intelligent Test Case Management Methodology
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