Wipro’s QET GenAI Accelerator infuses GenAI in Testing lifecycle by assisting at every step, addressing dependencies (like data) and producing test deliverables (like TCs, scripts) in completely automated manner with GenAI.

This significantly accelerates Testing and adds value by improving Test Productivity and experience for testing via increasing throughput, coverage on one hand and reducing cycle time on other hand.

Key differentiation involves flexibility of setting the flow of churning the reference, context and ensuring the relevance, accuracy of outcomes from GenAI with the right orchestration and improvisation of LLM responses.

Some key features / Testing Use cases facilitated by the accelerator:

Test Strategy: Formulating Test approach by taking inputs as Design, Requirements documents (BRD, SRD, HLD, LLD)

Test Design: Starting with User story - Generation of Test scenarios, Test cases, Test data, Automation scripts

Data Migration/ ETL Testing: Based on Data mapping tables create Test cases, SQL scripts for validation, Generate Data Mapping table from design documents

Test Execution Optimization: Impact Analysis, RBT, Regression optimization, Test failure causation, Defect resolution

Shift Left Quality: enhance User story contents, Generate User stories from Features, Test Design from Code etc

Intelligent analysis of defects and failure logs

AWS tools and service Integration:

• Amazon Bedrock for RAG on a pretrained LLM model

• Amazon Bedrock for AWS Lambda function for embedding

• AWS Open Search Vector Store

• AWS Lambda

• AWS S3