Igniting Application Testing with AI + Automation

Think 2018 / 8760 / March 19, 2018 / © 2018 IBM Corporation
Igniting Application Testing with AI + Automation
Session #8760

Please note
IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice and at
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Information regarding potential future products is intended to outline our general product direction and it should not be relied
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Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The
actual throughput or performance that any user will experience will vary depending upon many factors, including
considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage
configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results
similar to those stated here.

3
Todays Challenges
AI Enabled Approach
Explore the 3 Pillars
Bringing it all together

4
The Challenge
T H E S E
D R I V E
T E A M S I Z E
A N D T I M E
Test Case
Execution
How do you reduce the test
cases volumes ?
Defect
Volume
How can we eliminate defects and not
just shift left
Test Case
Automation
How can the automation be more effective ?
The fundamentals of the
quality operating model
will continue to be driven
by the same 3 pillars as
it is today

Gone are the times
where we can afford to
focus all our energy
and strategic thinking
on simply finding
defects
5
Test
Optimization
Detection
Rate
and
volume
Location-
mix
Standardise
process
Centralisation
/automation
Prevention
Maturity
Efficiencies QA TransformationLabour Efficiency
Value
Deep Defect
Analytics &
Prevention
AI Defect
Prediction
AI Defect
Classification
AI Knowledge
Management
Remove work
and automate
Improve
quality
Single
Enterprise
Quality
framework

IBM delivers an AI driven Quality Platform to optimize test
QA is enabled by a
platform that assembles
the pieces and can
manage controlled
distribution of the
process and
responsibility
6
IGNITE Quality Platform
- Single sign on
- Test Approach / Common Language
Enterpris
e data
Requirements
User Stories
Existing Test
cases
Business
Analysts
Architects
Developers
AUTOMATION ANALYZEOPTIMIZATION
AI INSIGHT
• Extract
• Define need
TECHNOLOGY – Automation / Virtualization / Performance
Test Model
Data Model
Test cases
REDUCE
OPTIMIZE
MODEL
TRANSLATE
Gherkin Tests
CONVERT
Test Executables
Selenium , SOAP UI, SQL
Issues
Defects
Results
EXECUTE
Application
knowledge
Real time
dashboard
AI Model
MINE
INGEST
Prediction/Prevent
ClassifyEnv.
Ready

Statistical modelling
and AI combine
together to understand
existing tests and
requirements to derive
effective test plans
using combinatorial
analysis.
7
Achieves
100%
coverage of
requirements
Achieves
60%
reduction in test
scenarios
1.TEST OPTIMIZATION
OPTIMIZATION
• Extract
• Define need
Test Model
Data Model
Test cases
REDUCE
OPTIMIZE
MODEL

“Everyone Automates”
employing Gherkin as
the connecting tissue
between the test plan,
provision of the test
data and the test case
automation.
8
Achieves
100%
automation ready to
drive continuous test
Achieves
70%
reduction in
automation effort
2. AUTOMATION
AUTOMATION
TRANSLATE
Gherkin Tests
CONVERT
Test Executables
Selenium , SOAP UI, SQL
EXECUTEEnv.
Ready

Traditional approaches
to defect analysis stop
short of actionable
recommendations.
AI provides the
assistance required to
develop action plans
addressing defect
patterns vs. individual
defects.
9
Achieves
85%
defect classification
accuracy
Achieves
20%
reduction in defects
3. ANALYSIS
9
ANALYZE
AI INSIGHT
Issues
Defects
Results
Application
knowledge
Real time
dashboard
AI Model
MINE
Prediction/
Prevent
Classify
INGEST

The IGNITE Quality Platform delivers…
… an integrated AI
enabled Quality
Management capability
that fundamentally
changes the dynamics of
the 3 drivers
- Single sign on
- Test Approach / Common Language
Enterpris
e data
Requirements
User Stories
Existing Test
cases
Business
Analysts
Architects
Developers
AUTOMATION ANALYZEOPTIMIZATION

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continued
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Igniting Application Testing with AI + Automation

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