Quality Engineering

We deliver integrated, holistic and innovative Quality Engineering services using decades of experience and built-for-purpose tooling.  We meet you where you are and help you mature, scale and innovate to get where you want to be.

With a ready-to-use test automation platform and a suite of tools and accelerators, we reimagine software testing for an age of disruption. Our team helps you spend less time on rote tasks through high-velocity automation while getting more insights out of data for greater innovation.

We take testing to the next level through quality engineering across the full lifecycle – from code quality and pipeline quality gates to performance, resiliency and post-production coverage feedback and everything in between.

Beyond the typical testing capabilities, we help you achieve true quality engineering through:
  • Shifting testing left (and right): Embedding quality throughout development and delivery to hypercare and post-production quality
  • Bespoke, fit-for-purpose solutions and tools using the latest technology
  • DevOps and Quality Engineering (DevTestOps) transformation and scaling


Quality Engineering - building quality into everything we do

At EY, Quality Engineering means taking testing to the next level by looking beyond how things have always been done to how things could be done using innovation and technology.

Quality Engineering value proposition chart
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    Line chart showing capabilities and value propositions on axes of innovation and maturity.

    The following capabilities increase as innovation and maturity increases: test automation; agile testing and strategy, bespoke QE solutioning and tooling, high velocity automation, full-lifecycle quality, automated data quality and profiling. These points are supported by thought leadership in quality engineering; impactful, purpose fit solutions; technology-enabled QR to transform how we deliver.

    The following value propositions increase as innovation and maturity increases: business or sector expertise, lower cost per test, and testing expertise, methods accelerators.

DevTestOps: testing early, testing often and testing throughout

DevTestOps is not a new methodology - it elevates the importance of testing in DevOps that is often overlooked. Quality should be integrated into the lifecycle, not added at the end.

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    Phases of the DevTestOps cycle include:

    • Merge
    • Code
    • Plan
    • Monitor
    • Operate
    • Deploy
    • Release
    • Build

    Key points include:

    • Unit tests, quality tooling, chaos engineering
    • Test the plan for infrastructure, orchestration, config and other related mechanisms
    • Production quality checks, canary testing, dogfooding, A/B testing
    • Leverage analytics and clickstream data from production use to feed testing and design
    • Testing coverage should align with production APM and other monitoring coverage
    • Load testing, cross-system testing
    • Functional, non-functional, data, integration, business process tests
    • Automated quality gates, checks


Service offerings


Key highlights

The journey from current state to Agile or DevOps requires successful deployment of enablers to support the transition. Moving quality to left in our product development life cycle dramatically decreased risk and speeds our ability to innovate.

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    Evolution of scrum models

    Key points:

    • Current state (transitioned from waterfall), includes product owner, scrum master, developers, tech test lead, business test lead, manual QA, automated QA, manual UAT, automated UAT. Testing happens separately for UAT/business process, is independent team(s), happens on the side, may be done in separate stories, may not be a part of DoD. Required enablers include scalable automation foundation, automated regression and optimized testing methodology
    • Optimized testing (focus on product quality together), includes product owner, scrum master, developers, tech test lead, business test lead, manual testers, automation testers. Testing is still independent team(s), consolidated coverage for functional and business, shared automation in CICD, and some testing sprint behind. Required enablers include agile maturity (quality DoD, acceptance criteria, etc), automation maturity and automation skills/training
    • Automation first (focus on automation) includes product owner, scrum master, developers, tech test lead, business test lead, automation-first testers. Testing is primarily automated in-sprint, tightly coupled with development, and has heavy use of CICD. Required enablers include DevOps maturity (toolsets, methodology changes, etc), automation maturity, skills/training
    • DevOps (Streamlined team for fast delivery) includes product owner, scrum master, developers/testers. Testing is a natural part of all work being done, fully automated release pipeline, and environments and data are virtualized.

When testing an application with high-velocity automation, you gain dynamic scaling of parallel test runners without adding infrastructure. Tests are performed across browsers, with screenshots captured and videos of executions.

As a cornerstone of these efforts, our capability in high-velocity automation helps you go from test design to a completely automated execution in mere days. You can get more coverage our of fewer tests and generate automated tests on demand and regenerate that automation with updates or new coverage.

This capability brings together:

  • Orthogonal arrays and statistical optimizations in test design
  • Gherkin tests with descriptions in an easy-to-understand language
  • Core automation framework that translates Gherkin into runnable code
  • Powerful capabilities to cover web, API and database tests
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    Chart describing how high velocity automation is delivered.

    First steps:

    • Go from test design to a completely automated execution in days
    • Provide highest coverage with least number of tests
    • Generate automated tests on demand
    • Test design optimization (TDO)
    • Maximized coverage with least number of tests using orthogonal arrays and statistical optimizations
    • Next steps:
      Generate BDD/Gherkin tests
    • Easy to understand English-like tests
    • Automation framework
    • Core framework capable of translating Gherkin to runnable code and leveraging powerful capabilities to cover web, API and DB costs

    Dynamic execution containers includes:

    • Automated test runners (various)

    Application under test includes:

    • Provides dynamic scaling of parallel test runners without adding infrastructure
    • Includes cross-browser testing
    • Captures screenshots and videos of executions

The Next Gen Testing Platform (NGTP) is a powerful yet simple platform for software testing.

The platform is built for the real world because it’s built on years of in-the-field EY testing across every industry sector.

  • Pre-built platform lets you start automating immediately 
  • Based on years of accumulated testing experience 
  • Customizable for your unique environment 
  • Automate testing for multiple technologies 
  • Intuitive user interface makes automation easy

There are many automated testing tools in the market. What makes the NGTP a better solution? Some tout a long list of features, but most are a poor fit for your business and technology teams doing the actual work. It turns out automation isn’t automatic.

  • Open-source libraries are free, but complex and technical
  • Off-the-shelf applications are not easily customizable and lock you in to an  expensive, license-based ecosystem
  • Neither includes real-world testing experience or offers a strategic approach

With NGTP’s pre-built, field-tested solutions, you get open-source possibilities and off-the-shelf ease.

Workbenches extend the capabilities of NGTP to provide high-impact, targeted value.

The workbench enhances NGTP with bespoke test automation assets built for specific use cases such as new implementations or upgrades to specific platforms, applying advanced analytics or machine learning or large-scale data testing. The workbenches contain test design, execution and reporting capabilities that integrate seamlessly with the NGTP such as data mining for application configuration to automatically generate test scripts, on demand data generation, etc.


Reduction of automation ramp-up*


Reduction in test design efforts*


Reduction in retesting and regression efforts*

Workbench name Description
Data  validation

Validate millions of records with complex transformations in minutes using English-like test steps and identify variations and mismatches.

Use cases include:

  • Cloud migrations
  • GL/ledger reconciliation
  • ETL validation and data conversions
Test intelligence

Apply machine learning, NLP, predictive modeling and advanced analytics to testing.

Use cases include:

  • Predictive modeling for test execution and planning
  • Effect root cause analysis using NLP
  • Translate manual test steps to test automation using NLP
  • Intelligent exploratory testing bots
  • Manual test case normalization and standardization
  • Production incident analysis for missing test coverage
Test data management and analytics

Take TDM to the next level to include data quality and profiling as inputs to test design and automatically identify data for test automation. Automatically identifies bad data and enables domain-based test design.

Use cases include:

  • Financial regulatory reporting
  • Optimizing test design based on actual data
  • Creating ecosystem of data feeding to/from testing
Document validation

Perform visual, content or template validations at scale.

Use cases include:

  • Document generation validation (statements, declarations, reports. account docs, etc)
  • Regression testing to new document generation provider
  • Comparison between docs and SOR
Event Driven Architecture

Pre-built components and test steps for event processing and AVRO/JSON message generation.

Use cases include:

  • Any EDA project using Kafka or Azure Event Hub
Load testing as a service

Container-based solution for distributed JMeter performance testing supporting automated deployment, execution, results consolidation and teardown on demand or in a CI/CD pipeline.

Use cases include:

  • Performance testing as quality gates
  • Scaled distributed load testing at no cost

Use EY’s custom built SAP GUI driver and our library of 100s of industry-specific test scenarios to quickly stand up SAP test automation that would otherwise require paid vendor tools.

Use cases include:

  • ECC upgrades
  • SAP cloud migrations and new implementations

Enables a transformational shift in approach to testing – faster, more coverage and just better. Automatically generate automated tests based on your unique configuration.

Use cases include:

  • New guidewire implementations
  • Guidewire version upgrades
  • Automatically generating statistically optimized automated regression suites

No code test automation for Unqork’s no-code app dev platform. This workbench generates object locators, unit tests and functional test steps for any Unqork module for import into NGTP.

Use cases include:

  • “Automation-first” in-sprint testing
  • Unit, functional and end to end testing of Unqork modules and workflows

What is in a Workbench?

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    what is in a workbench

    First level includes platform- or application-specific assets, custom accelerators, and real-time test data mining and config. Extraction.

    Bar chart showing increase value added. Other options dictate modest value added, The Next Gen Testing Platform shows greater value added, The Next Gen Testing Platform + workbenches shows significant value added with increasing future potential.


Test talk series

Scroll through the video gallery to watch videos on these topics:

  • Introduction to Test Talk
  • Test automation drivers
  • Self-healing test automation
  • Pairwise testing
  • ROI-based test automation

      Innovation and demos

      Scroll through the video gallery to watch demos of the following:

      • Fully automated test design and execution
      • Secure Remote Checkout (SRC) specification coverage optimization and test automation
      • Using NLP for defect root cause analysis

      Contact us

      Like what you’ve seen? Get in touch to learn more.