The science of analytics is applied extensively to predict challenges that arise in operations and product quality. This intelligence can be simulated for IT and Quality Assurance functions to achieve higher efficiencies and product quality. QA teams have established exhaustive ways and implemented tools to capture and report metrics pertaining to efforts, data and testing results. However intelligence around quality and operational aspects requires human intervention for decision making. Statistical techniques and analytical procedures can be applied across QA activities to strengthen this intelligence. For instance, in statistical models such as OATS, MCDC are being deployed in the QA planning and operations stage for accurate estimation and effort optimization. Analytical techniques including regression analysis, clustering and factor analysis are helping teams build defect prediction models. Using analytical techniques, organizations can build models for data and code visualization. These have enabled IT organizations to monitor and maintain defect-free software whilst making the code fix easier and more efficient. QA analytics is getting extended to self-healing systems and robotics for QA. It’s important that QA teams start building expertise around these analytical models as they are likely to transform the way testing is performed and consumed today.
In this session you’ll learn about:
- Statistical models applicable for QA functions across the software lifecycle;
- Mechanisms to effectively capture and analyze data for Quality intelligence;
- Current tools and emerging frameworks that complement QA analytics;
- Analytics and a prologue to self-healing codes and QA robotics.
With 25-years of management consulting experience in IT Process and Quality Transformation, Jim leads Cognizant’s Global Process and Quality Consulting practice, focused on high-end process and quality transformation value propositions for new and existing customers. Prior to joining Cognizant, Jim was Vice President of Quality at Transunion, responsible for quality at the enterprise level, driving the implementation of a $150 million IT transformation program. Prior to that, Jim was a practice lead, senior executive at Bearing Point and Diamond Management Consultants, leading strategic process and quality initiatives at Fortune 500 companies. Jim holds a B.S. in Industrial Engineering from University of Illinois and a M.B.A. from University of Chicago.
Sripriya (Priya), heads the strategy, marketing, and operations for Cognizant Testing Services. She is also responsible for business development for emerging markets. With over 15 years of experience in IT and management consulting for Fortune 100 clients across the globe, Priya’s specialties include quality management, outsourcing, new business development, SDLC, software project management, business analysis, quality assurance, vendor management, PMP, six sigma, PMO, and management consulting. Pursued as a thought leader in the field of software testing, Priya is a regular presenter at prestigious conferences such as Software Quality Engineering (SQE), QAI - Florida and Toronto, SQS - UK and Australia, Swiss Testing Day, Laboratory of Quality Software, The Netherlands. She is an alumnus of Harvard Business School.