Accelerating Your Organization Success with Advanced Quality Engineering

Assessing an organization's Quality Engineering Maturity is crucial for delivering high-quality products and services. It involves evaluating testing practices, methodologies, tools, and overall quality culture. Let's explore the importance of this assessment, key stakeholders' involvement, and the journey towards achieving higher levels of quality maturity.

• Define Quality Engineering Maturity and its significance in today's business environment.
• Emphasize the role of Quality Engineering in delivering high-quality outcomes.
• Describe Quality Engineering Maturity as a continuous journey of improvement and adaptation.
• Highlight the importance of assessing an organization's quality maturity level.
• Discuss the involvement of key stakeholders in the assessment process.
• Mention the need for customization and flexibility in the assessment approach.
• Emphasize the creation of a comprehensive report and roadmap for enhancing quality maturity.

Process and Culture

Automation Methodology

QA Infrastructure Scalability

CI/CD Integration

TEM, TDM

1

Starting

• Conventional QA methodologies
• Segregated Dev and QA teams
• Limited touchpoint with product teams

• Manual GUI based testing
• Heavy reliance on a "few experts"
• Best can Certify a release in few weeks

• Leverage IT team to spin up infrastructure needs
• Continuous bottle necked on unavailability of test infrastructure

• Effective vertion control & build automation for code development

• Automation failing frequently due to environmental & test date issues
• Hard-coded test data in the scripts

2

Improving

• Documents Process
• Adopt a hybrid approach to QA (waterfall + Agile)
• Increased collaborations with other teams

• Higher reliance on functional and GUI based testing
• Low degree of coverage
• Adopt a hybrid approach to QA (Waterfall, + Agile)

• Leverage basic virtualization in test technology
• Still dependent on IT and bottlenecked

• Leverage a CI tool for triggering builds

• Data driven scripts
• Tests frequently foil due to lack of correct test data

3

Establishing

• Extend team collaboration
• Strong Agile process
• Dev & Test - One team
• Processes flow across Dev / QA / Build & Operations

• Higher coverage with GUI Functional! testing
• Some automated tests at service layer
• Final Certification is with Manual "experts"

• Fully virtual independent test infrastructure set up and deployment
• No dependency and bottleneck on infrastructure

• Auto triggered builds on code check-in
• Build basic code quality and unit test gates in CI

• Leverage service virtualization to achieve automation
• Evolved test data strategy & tooling

4

Adopted

• Single owner in an integrated team - Unified view of QA between dev and QA
• Iterative Development & Integrated Plan

• Automated Integration test
• Automated Unit level test
• Comprehensive Coverage thru automation
• Adopt BDD/ATDD process

• Leveraging cloud-based services and deployments across cross functional teams
• Potentially Leverage commercial on-demand/cloud test infrastructure

• Full automatic acceptance test integrated in the main CI pipeline
• Automatic performance parameters in CI

• Basic service virtualization using mock objects and stub services.
• Completely automated relevant test data generation.

5

Continuous
Improvement

• Metrics based real time dashboard
• Automated Quality Health Checks - Supports Go/No Go Decisions

• Automation at different levels (unit, headless, GUI, services)
• Integrated with CI/CD
• Leverage in-sprint Automation

• Test infrastructure as code
• Leverage containers to reliably reproduce test nodes
• Leverage cloud to setup, tear-down and scale up nodes on demand

• Leverage containers to reliably deploy
• Integrated quality gates for code quality, unit tests, code coverage and acceptance test
• Automated promotion

• Advanced tool-based service virtualization
• Machine learning based automation

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