With growing software quality and release acceleration challenges, organizations are shifting their approach from ‘quality assurance’ to ‘quality engineering’, which ensures first-time right quality. This transformation can be achieved through smart application of artificial intelligence (AI), automation, and integration of tools across ecosystem. When implemented correctly, these promise huge cost savings and major reductions in go-to-market timelines.
Tata Consultancy Services’ Smart Quality Engineering (SmartQE) is a unique AI-based solution, designed to engineer quality upfront at high velocity. Designed on the principles of ‘integration, intelligence, and automation’, the solution optimizes the quality-engineering lifecycle through contextual insights and actionable outcomes. Using cutting-edge AI and machine learning algorithms, SmartQE can improve decision-making and enable automation in functional, non-functional, and test data environments. The solution includes:
- Intelligent assurance – application of advanced AI and machine learning methods such as natural language processing, artificial neural networks and linear regression for incident analysis, defect prediction and test suite optimization
- Release orchestration – digitized release workflow with quantitative assessment of release quality
- Test environment management – automated provisioning, monitoring, scheduling and auto heal of incidents
- Test data management - provision test data on demand and data virtualizion for data privacy and reuse
- QE bots - contextual analytics-based insights with QE index and test debt reduction
- Engineered quality : Eliminate waste through analytics and LEAN models, achieving up to 40% reductions in the cost of quality.
- Transform process fragmentation: Overhaul traditional quality assurance approaches and transition to an engineering-centered paradigm.
- Collaborate across units: Enable seamless handover and significantly cut down on manual dependencies, using bots.
- Accelerate deployment: Increase business agility with intelligent automation throughout the QE pipeline, reducing cycle times by around 35%.