The document discusses the integration of AI and robotics in software testing, highlighting the benefits of intelligent automation systems and their ability to enhance quality assurance through data analytics, machine learning, and autonomous frameworks. It emphasizes the need for organizations to adapt to evolving digital landscapes and implement smarter automation strategies amidst challenges such as requirement changes and data complexity. The future of QA involves a shift towards proactive, predictive analytics that optimize testing processes and improve overall efficiency.

1. #ATAGTR2017
16th 17th March
AI in Software Testing
Ramakrishnan Venkatasubramanian
Cognizant Technology solutions

2. Agile Testing Alliance Global Testing Retreat 2017
The Promise of AI and Robotics
Intelligent Robots help humans to be
efficient
Software Testing is a goldmine for AI &
Robotics

3. Agile Testing Alliance Global Testing Retreat 2017
Organizations are Confronted with a New Dilemma
The digital revolution
An assorted demography
Oceans of data
First mover’s advantage
Newer business models

4. Agile Testing Alliance Global Testing Retreat 2017
To Address these Paradigms, Enterprises Need a New
Approach to Quality Assurance
A redundant past Seamless Today Futuristic Tomorrow
Test Manually Automate End to End Bot-led automation
AI and Analytics are transforming traditional Test Automation to Smarter Automation

5. Agile Testing Alliance Global Testing Retreat 2017
AI
Automation
..That Encompasses The Entire Test-Lifecycle
AutomationMaturity
Record &
Playback
Use & Reuse
of Functions
Data driven
frameworks
Key words
driven
frameworks
Script-less
Automation
Test Data
Automation
Process
Automation
E2E
Automation
Test Design & Execution
Middleware
Automation
Automation across Lifecycle
Conventional Automation
Non Conventional Automation
Futuristic Automation
Timeline
Future

6. Agile Testing Alliance Global Testing Retreat 2017
However, this Journey is Full of Challenges…
Environment
Downtime
Requirement
Changes
Defect
Management
Data
Management
Information
Exchange Rate
End to End
Traceability
100% error-less code is unrealistic
20% of time induced for interaction at PA-
QA level *microfocus.com
10% of STLC time is wasted on downtime
*microfocus.com
Varies on the SDLC methodology followed –
<20%
10% of the Defects arise the need of a
requirement change
Sanity check before being utilized. 70% of
the test data remains invalid
Source:
*World Quality report 2014-15
https://www.microfocus.com/assets/testing-its-invisible-giant_tcm6-200416.pdf
http://www.evoketechnologies.com/blog/software-testing-trends-predictions-2015/
https://www.capgemini.com/thought-leadership/world-quality-report-2014-15

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and Implementation Issues…
Environment
• Integrated Environments
• Data complexity
• 24x7 Availability
Technology
• Diverse Platforms
• E2E Integration Scenarios
• Newer technologies
Skills
• Frequent Up-skilling
• Technology Orientation & Multi-skilling
Methodology
• CI and CD
• Defect prevention

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Breakthroughs in Process Intelligence Create Opportunities
Economical
Reduce QA effort/costs
Intelligent
Smart capabilities, meaning s/w
can ‘think’ and ‘learn’ on their own
Efficient
Optmize coverage and improve
Quality Intelligence makes your QA smarter

9. Agile Testing Alliance Global Testing Retreat 2017
The Answer - Intelligent Automation systems
Traditional Automation
Autonomic system
End to End Automation
1
2
3
0%
(-25%)
60%+
TCO reduction
Levelofautomation
(-45%)
40%
1. Autonomic Automation
2. Cognitive Automation
3. Predictive Analytics

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MACHINE LEARNING
NATURAL LANGUAGE
PROCESSING
AUTONOMOUS FRAMEWORKS
CONTAINERIZATION &
DEPLOYMENT AUTOMATION
EMERGENCE OF LIFECYCLE
AUTOMATION
Have we looked at the factors contributing to
leakage, optimal test coverage?
How can we Automate the automation
process and reduce hand-offs
Artifact driven, baseline and auto compare,
self heal capabilities, scriptless approach
How can test teams help increase velocity,
partner with Ops for validation, certification
Integrated harmonized approach with tools and
frameworks, frictionless E2E automation
..That are Mature and Assure a ‘Defect-free’ Eco-system

11. Agile Testing Alliance Global Testing Retreat 2017
1. Autonomous Automation is Intelligent and
Adaptable to Change
Trigger/
Scheduler
AI SystemDeveloper
• Code refactoring or bug
check-in
• Correlates this information
to tests suite and identify
the impacted test cases
• Computes changes done,
affected files & sub systems
• Run selected tests
 Interactive collection of autonomic elements
 Self govern and high level of adaptability to change
Intelligence
 Increase predictability
through self learning
 Improve quality
through analytics &
robotic automation
 Perform tests based on
business rules
 Overall IT cost
reduction
 Enables companies to
use their IT assets in a
more strategic manner
Key Benefits

12. Agile Testing Alliance Global Testing Retreat 2017
Self Managing
Self
Configuration
Self Optimization
Self Protection
Self Healing
…with the Ability to Self Act, Regulate and Learn
React to varying &
unpredictable conditions in
operating environment
Self-Configuring, Self-
Healing, Self-Optimizing and
Self-Protecting
Detect and to optimize
suboptimal behaviors
Detect problems and/or
failures and to recover from
them
Protect itself from both
external and internal factors

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2. Cognitive Automation Emulates Human Execution for
Repetitive Processes
Ease and accuracy
in gathering and
organizing data
Aids advanced
analytics
Accuracy in
prediction
High performance
Enables efficiency
improvement
Time, Cost and
People reduction
Key Benefits

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Through Natural Language Processing and Machine
Learning
HIGHLIGHTS
 Autonomous generation of scripts
 Better maintainability and ease of
script modification
 Time-stamped selenium scripts – for
versioning
 Reduction in tables of test data for
the application under test
Application
Under Test
To re-organize objects
NLP Engine
(Knowledge DB)
Parse URL to
pull objects
Object mapped
& Selenium
Test Cases in
Excel / XML / UML
Automation
Script Creation
AI Agent
Parse Test Cases

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3. Insights Enable Higher Predictability Across the Life Cycle
Cognitive
Test
Execution
Test
Optimization
Test
Design
Quality
Insights
EliminateRote
BuildIntelligence
Non-Cognitive
Repetitive
Non-Repetitive
Image Source:
https://www.dreamstime.com/illustration/programmable.html

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…and help optimize quality at every stage of the SLC
Requirements Coding & Unit Testing System & SIT Operations Customer Feedback
End
Customer
Insights
Assure Immersive
Customer
experience
Operational
Insights
Correlate
transactions to
test design
Testing
Insights
Proactively
Plan the Test
Process
Development
Insights
Eliminate
Non Productive
Testing
Business
Insights
Greater Business
Requirements
Coverage

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Case Study : Generating Quality Insights from Upstream data
Client: One of the largest motor clubs and travel insurance organizations in North America
• Frequent requirements
changes
• Agile development
• Incessant schedule slippages
BACKGROUND SOLUTION BENEFITS
Cognizant’s delivered an
Analytics Driven QA solution
• API based integration of
Testing tools
• Developed Stability index
to predict schedule
slippage
• Real time schedule
prediction through
analytics
SCHEDULE PREDICTABILITY
Up to 3 days
TEST COVERAGE
30% increase
APPLICATION STABILITY
81% higher

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To Summarize
Next-Gen Technology: A
strategic enabler for
organization
Co-relate Analytics data to
anticipate changing business
needs (Quality bots are the
future)
AI & Predictive Analytics address
QA organization's strategic &
operational challenges
Techniques like NLP
enable Dual-shift of
quality

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Unleash Predictive Analytics to Enhance Business Value
Predictive
analytics
Descriptive
Analytics
Diagnostic
Analytics
Prescriptive
Analytics
Deep
Learning
Analytics 1.0 Analytics 2.0 Analytics 3.0
What is the defect trend
in the last year
What are the top causes
behind the defect?
What defects are likely
to leak in production?
What approach should we take to
prevent these defects from leakage?
Have you looked at all the factors
contributing to this defect leakage?
Analytics facilitates realization of business objectives through reporting of data to analyze trends,
creating predictive models for forecasting, and optimizing business processes for enhanced performance

20. Agile Testing Alliance Global Testing Retreat 2017
Artificial Intelligence and Predictive Analytics will Play a
Vital Role in the Future
Use of AI &
Analytics in
Business:
• Utilizes analytics to understand and predict end user
behavior
• Machine learning enables continuous improvement to
system responses based on dynamic user behavior
• Analytics and ML together make continuous automation
improvement a reality
Why AI &
Analytics
based
QE&A
• Focus on defect prevention rather than reactive approach
• Proactive & Intelligent Testing
• Focuses on what’s most important especially in an
increasingly Agile & DevOps world
Analytics is the process of
acquiring insights from the
systematic analysis of data
patterns and statistics
AI & Analytics will play a pivot role
in QA Organizations to make
testing smart, lean and proactive
with each cycle. It will also provide
insights into ‘What ought to be
tested?‘ rather than ‘What can be
tested?’

21. Agile Testing Alliance Global Testing Retreat 2017