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By Manisha Mittal – Quality Assurance Consultant
Intelligent Digital Mesh
QA & Testing
Copyright © 2019, Nagarro. All rights reserved.
2
Agenda
1. Understanding intelligent hyper connected environment
2. Intelligent digital mesh across domains
3. Challenges and opportunities in Quality Assurance
4. Evolution in testing approaches
5. Benefits of AI/ML and analytics in digital mesh testing
6. Focus areas & tools for testing Intelligent apps
7. Intelligent testing landscape: Optimize test cycles
8. Intelligent testing approach
9. Challenges & Solutions
10. Business benefits of intelligent digital testing
Understanding intelligent hyper connected environment
An Intelligent system that can do
intelligent things with:
• Technologies like Artificial Intelligence, Machine
Learning, Deep Learning, Natural Language
Processing
• Techniques that make smart machine
understand, learn, predict, adapt, operate
autonomously.
Digital consists of:
• Virtual & Augmented Reality
• Conversational platforms
• eGaming, movies & music, e Ticketing,
automation & Control, healthcare and e
communication
Mesh connects people, devices,
content & services together through:
• Mobile devices
• Wearables
• Electronic devices
• Mobile testing
• Device testing: Wearables, Electronic devices
• Scalability and performance testing
• Regulatory compliance testing
• Analytics (AI/ML) validation
• Intelligent test case generation
Digital Assurance focus areas:
3
4
Intelligent digital mesh across domains
• Robot assisted surgeries
• Personalized health monitoring using
smart watchesHealthcare
• Risk analytics & regulation
• Managing client satisfaction
• Portfolio managementFinancial
• Dynamic pricing
• Social media feedback analysis
• Customer feedback analysisHospitality
• Demand forecasting
• Process optimisation
• Condition MonitoringManufacturing
• Recommendation engines & campaign
analytics
• Inventory planning
• Better customer service with reduced
response time
Retail
• Loyalty program and campaign analytics
• Route planning and optimization
• Better customer service by reducing
response timeTravel
• Smart supply and demand optimization
• Power usage analytics
• Customer specific pricing
Energy
5
Challenges and opportunities in quality assurance
• Spread of intelligent technologies leading to significant change in our lives
• With intelligent technologies increasingly disrupting the business models, small companies
pose a challenge to large corporate houses
• Significant increase of internet traffic with spread of mobile telephony and interconnected
devices
• Plethora of hardware & software devices/dependency on technology for day to day needs
• Requires anyplace, anywhere, and anytime connectivity on any device and with any service
6
Evolution in testing approaches
7
• AI can write scripts and analyze large amounts of
data sets faster
• AI can handle sorting through log files, saving time
and enhancing correctness in the program
tremendously
• AI can help in eliminating more bugs
• ML approach, which will offer more reliable
outcomes than traditional testing
• ML analyzes customer data for a more proper
understanding of the most recent products and
features that customers need
Benefits of AI/ML and analytics in digital mesh testing
8
Focus areas & tools for testing Intelligent apps
9
Intelligent testing landscape: Optimize test cycles
Skills Required Test Parameters Test Goals Best Practices
• Bot identifies the assets
and helps generate test
cases from requirements
• Good grasp of statistical
concepts
• Capabilities in data
analytics
• Knowledge of computer-
hardware architectures
• Know-how of languages
such as R, Python, Java,
etc
• A/B testing
• Metamorphic testing
• Predictive Analysis
• Cognitive QA testing
• Predictive QA
dashboards
• Intelligent QA
automation
• Continuous testing
• Smart QA analytics
• Defect Analytics
• Log Analytics
• Continuous Improvement
• Design specific test
approach
• Perform usability testing
• Ensure security &
customer exp.
• Assure range & frequency
• Ensure performance
• Simulate usage scenarios
• Use real devices
• Ensure uninterrupted
data transmission &
collection
• Deploy network
simulation tools
• Increase levels of
automation
• Implement non-silo
approach for test
environment and data
provisioning
• Re-skill QA engineers
• Improve tracking to
optimize processes
• Data security as per
complaints
Intelligent testing approach
• Bot identifies the assets and helps generate
test cases from requirements.
01Identify
• Bot identifies the duplicate test cases &
optimizes test scenarios using AI & ML.
02Optimize
• Bot automates environment setup
• Bot accepts & validates coding standards,
execution status
• Bot integrates data from all cycles
03Automate
• Bot analyses results and test performance.
• Bot predicts future defects based on historical
data
04Analyze
10
11
Identify Optimize Automate Analyze
• Bot identifies the assets
• Helps in generating the test cases from
requirements
• Analysis of existing test cases, data
• Combines value from different attributes
along with business rules
• Achieves 100% coverage of business
variations of application
12
Identify Optimize Automate Analyze
• Optimize number & types of tests to achieve
100% coverage
• Search, Tagging and Modeling: This model finds
duplicate test cases & groups them together into
what we call a cluster
• Attributes & values found in these clusters are
used in test optimization
• Optimal set of test cases are generated which
represent 100% coverage of business variations
of application
• Build a repository of optimized test suites that
could be used repeatedly
13
Identify Optimize Automate Analyze
• Actual automation in cucumber format is
generated from optimal test-set, which is
integrated into automation framework
• Analysis between sprints is done to get 100%
coverage. It includes modifying the original set
of test cases and eliminating redundant test
cases
• Search test data catalogue and match the data
which is needed for automation
• Map objects with xpath and store objects
14
Identify Optimize Automate Analyze
• AI analyzes defects and identifies the patterns
of defects & helps prevent them in future
• Cognitively identifies the origin of the defect in
real-time & classify it as code or no code defect
• Works together to reduce test cases & defects
with lower cost, increase speed and quality
with 100% coverage
15
Challenges & proposed solutions
16
Business benefits of intelligent digital testing
• Predict, prevent, and automate the
process using self-learning algorithms
• Test suite optimization & identify of
high risk areas for risk-based
prioritization
• Identify hotspots & automatically
executing test cases
Improved quality
• Quicker time to market: Speed-up
release of new products and services
• Identify and remediate compliance
gaps transparently
More efficient, secure &
resilient
• Reduced cost of operations
• Bots perform complex tasks
Increased revenues and
profits
• Deliver services when requested
• Identify and remediate compliance
gaps transparently
Availability & reliability
• Enables organizations to quickly turn
data into actionable insights for better
decision making
• Mitigate business and technical risks
• Monitor for rapid and cost-effective
scalability of operations
Improve end-user satisfaction
and customer loyalty
• Bots are dynamic as they automatically
discover and evaluate every new feature
in the product
• Bots analyzes the application from end
user prospective and record
performance
• Bots builds, execute phenomenal
amount of test cases within minutes
Optimal test coverage
17
THANK YOU

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Intelligent Digital Mesh Testing

  • 1. By Manisha Mittal – Quality Assurance Consultant Intelligent Digital Mesh QA & Testing Copyright © 2019, Nagarro. All rights reserved.
  • 2. 2 Agenda 1. Understanding intelligent hyper connected environment 2. Intelligent digital mesh across domains 3. Challenges and opportunities in Quality Assurance 4. Evolution in testing approaches 5. Benefits of AI/ML and analytics in digital mesh testing 6. Focus areas & tools for testing Intelligent apps 7. Intelligent testing landscape: Optimize test cycles 8. Intelligent testing approach 9. Challenges & Solutions 10. Business benefits of intelligent digital testing
  • 3. Understanding intelligent hyper connected environment An Intelligent system that can do intelligent things with: • Technologies like Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing • Techniques that make smart machine understand, learn, predict, adapt, operate autonomously. Digital consists of: • Virtual & Augmented Reality • Conversational platforms • eGaming, movies & music, e Ticketing, automation & Control, healthcare and e communication Mesh connects people, devices, content & services together through: • Mobile devices • Wearables • Electronic devices • Mobile testing • Device testing: Wearables, Electronic devices • Scalability and performance testing • Regulatory compliance testing • Analytics (AI/ML) validation • Intelligent test case generation Digital Assurance focus areas: 3
  • 4. 4 Intelligent digital mesh across domains • Robot assisted surgeries • Personalized health monitoring using smart watchesHealthcare • Risk analytics & regulation • Managing client satisfaction • Portfolio managementFinancial • Dynamic pricing • Social media feedback analysis • Customer feedback analysisHospitality • Demand forecasting • Process optimisation • Condition MonitoringManufacturing • Recommendation engines & campaign analytics • Inventory planning • Better customer service with reduced response time Retail • Loyalty program and campaign analytics • Route planning and optimization • Better customer service by reducing response timeTravel • Smart supply and demand optimization • Power usage analytics • Customer specific pricing Energy
  • 5. 5 Challenges and opportunities in quality assurance • Spread of intelligent technologies leading to significant change in our lives • With intelligent technologies increasingly disrupting the business models, small companies pose a challenge to large corporate houses • Significant increase of internet traffic with spread of mobile telephony and interconnected devices • Plethora of hardware & software devices/dependency on technology for day to day needs • Requires anyplace, anywhere, and anytime connectivity on any device and with any service
  • 7. 7 • AI can write scripts and analyze large amounts of data sets faster • AI can handle sorting through log files, saving time and enhancing correctness in the program tremendously • AI can help in eliminating more bugs • ML approach, which will offer more reliable outcomes than traditional testing • ML analyzes customer data for a more proper understanding of the most recent products and features that customers need Benefits of AI/ML and analytics in digital mesh testing
  • 8. 8 Focus areas & tools for testing Intelligent apps
  • 9. 9 Intelligent testing landscape: Optimize test cycles Skills Required Test Parameters Test Goals Best Practices • Bot identifies the assets and helps generate test cases from requirements • Good grasp of statistical concepts • Capabilities in data analytics • Knowledge of computer- hardware architectures • Know-how of languages such as R, Python, Java, etc • A/B testing • Metamorphic testing • Predictive Analysis • Cognitive QA testing • Predictive QA dashboards • Intelligent QA automation • Continuous testing • Smart QA analytics • Defect Analytics • Log Analytics • Continuous Improvement • Design specific test approach • Perform usability testing • Ensure security & customer exp. • Assure range & frequency • Ensure performance • Simulate usage scenarios • Use real devices • Ensure uninterrupted data transmission & collection • Deploy network simulation tools • Increase levels of automation • Implement non-silo approach for test environment and data provisioning • Re-skill QA engineers • Improve tracking to optimize processes • Data security as per complaints
  • 10. Intelligent testing approach • Bot identifies the assets and helps generate test cases from requirements. 01Identify • Bot identifies the duplicate test cases & optimizes test scenarios using AI & ML. 02Optimize • Bot automates environment setup • Bot accepts & validates coding standards, execution status • Bot integrates data from all cycles 03Automate • Bot analyses results and test performance. • Bot predicts future defects based on historical data 04Analyze 10
  • 11. 11 Identify Optimize Automate Analyze • Bot identifies the assets • Helps in generating the test cases from requirements • Analysis of existing test cases, data • Combines value from different attributes along with business rules • Achieves 100% coverage of business variations of application
  • 12. 12 Identify Optimize Automate Analyze • Optimize number & types of tests to achieve 100% coverage • Search, Tagging and Modeling: This model finds duplicate test cases & groups them together into what we call a cluster • Attributes & values found in these clusters are used in test optimization • Optimal set of test cases are generated which represent 100% coverage of business variations of application • Build a repository of optimized test suites that could be used repeatedly
  • 13. 13 Identify Optimize Automate Analyze • Actual automation in cucumber format is generated from optimal test-set, which is integrated into automation framework • Analysis between sprints is done to get 100% coverage. It includes modifying the original set of test cases and eliminating redundant test cases • Search test data catalogue and match the data which is needed for automation • Map objects with xpath and store objects
  • 14. 14 Identify Optimize Automate Analyze • AI analyzes defects and identifies the patterns of defects & helps prevent them in future • Cognitively identifies the origin of the defect in real-time & classify it as code or no code defect • Works together to reduce test cases & defects with lower cost, increase speed and quality with 100% coverage
  • 16. 16 Business benefits of intelligent digital testing • Predict, prevent, and automate the process using self-learning algorithms • Test suite optimization & identify of high risk areas for risk-based prioritization • Identify hotspots & automatically executing test cases Improved quality • Quicker time to market: Speed-up release of new products and services • Identify and remediate compliance gaps transparently More efficient, secure & resilient • Reduced cost of operations • Bots perform complex tasks Increased revenues and profits • Deliver services when requested • Identify and remediate compliance gaps transparently Availability & reliability • Enables organizations to quickly turn data into actionable insights for better decision making • Mitigate business and technical risks • Monitor for rapid and cost-effective scalability of operations Improve end-user satisfaction and customer loyalty • Bots are dynamic as they automatically discover and evaluate every new feature in the product • Bots analyzes the application from end user prospective and record performance • Bots builds, execute phenomenal amount of test cases within minutes Optimal test coverage