The panel discussion will focus on the : Trends of Big Data, Cloud, IOT and other key areas. Software Engineering, Agile , Continuous Delivery and Quality Engineering best practices. Reimagining Quality through usage of the right Process, frameworks, tools and overall Quality Management System.

1. Anish Cheriyan
Quality Leader, Harman
(Moderator)
Jagdish Singh Babra
Technical Lead, Google
Prasanna V
Architect, Oracle
Quality 4.0- Panel Discussion on Reimagining Quality
The panel discussion will focus on the :
• Trends of Big Data, Cloud, IOT and other key areas.
• Software Engineering, Agile , Continuous Delivery and Quality Engineering best practices.
• Reimagining Quality through usage of the right Process, frameworks, tools and overall Quality Management System.
28 Nov 20 | Saturday | 10:00 am- 12:00 pm
Sojan James
Distinguished Engineer, Harman

2. • Anish Cheriyan has wide Experience in ICT & Automotive Domains. He is associated with Harman Automotive as Head-
Quality and Engineering Tools.
• Prior to joining Harman, He has been associated with organizations like Huawei, Hewlett Packard and others in past.
Anish is Chair- American Society of Quality- ASQ (Bangalore LMC), Executive Council Member-BSPIN and an IEEE
member. He has been an Active Volunteer for Agile India, Agile Test Alliance, ASQ and other communities.
• Anish has completed Doctorate Research (PhD) in Software Quality Assurance in Agile Continuous Delivery and has also
filed patents in India Patent office and WIPO. He also holds Masters Degree in Computer Applications.
Anish Cheriyan
Harman Automotive

3. Introduction – Industry 4.0
Image Credit : https://dzone.com/articles/industry-40-the-top-9-trends-for-2018
Industry 4.0 has the
power to positively
impact Industries by:
• Enhancing
computational power
and connectivity
• Promoting human-
machine interaction
• Focusing on analytics
and intelligence
• Encouraging advanced
production methods

4. Quality 4.0- Perspectives
11/28/2020 4
Quality 4.0
Artificial
intelligence
Big data
Blockchain
Deep
learning
Enabling
technologies
Machine
learning

5. Industry 4.0 Design
Principles
Decentralized Decisions Information Transparency
InterconnectionTechnical Assistance
Ability of the systems to support humans through
comprehensive aggregation and visualization of
information for better decision-making and quick
solutions to problems.
Ability of cyber-enabled systems to independently
come up with decisions and carry out their dedicated
functions
information systems should be able to create virtual
copies of the physical world by configuration of digital
data into sensor data.
Ability of machinery and related components to connect
and communicate with people through the Internet
• Virtual Assistance
• Physical Assistance
• Collaboration
• Standards
• Security
• Data Analytics
• Information Provision
Industry 4.0 - Design Principles

6. QUALITY 4.0 – Value Proposition
11/28/2020 6Reference: Connected, Intelligent, Automated: The Definitive Guide to Digital Transformation and Quality 4.0

7. CQMS- Continuous Quality Management System
11/28/2020 7
R&D Manufacturing Supply Chain Customer
Real Time Information*
Design for
Quality
Real Time
Information
Analytics (ML/AI)
& Human
Intervention
Corrective &
Preventive Action
Learning
Organization (QMS)
…

8. Quality By Discovery
11/28/2020 8
PM Tools
CRM Tool
..
Defect
Mgmt
Tools
CI /CD
Tool
HR Tool
Aggregated
View- Real Time

9. Research on SQA body of Knowledge Gap (Agile Continuous Delivery)*
11/28/2020 9
Around 100 participants across various software organization took the survey followed up with Interviews
>80% mentioned that Quality body of knowledge (SQA) lacks the details about Agile CI/CD approach
Code quality
4%
Lessons learnt issues
4%
Lack of effective planning
3%
Non Functional "ities"
assurance
4%
Open Source Adoption & Cyber
Security issues
12%
Culture Building issues
6%
In Phase quality assurance
issues
6%
Life Cycle Definition & Agile
Implementation issues
16%
QA Planning and Lack of
effective audit, Too much
Governance
17%
Competency issues /Domain &
Technical Knowledge
14%
Continuous Delivery
implementation issues
14%
*Research Study (Doctoral Research) on Software Quality Assurance practices in Agile continuous delivery- Anish Cheriyan

10. Agile Continuous Integration and Delivery (ACID)-QA model
ACID Quality Model comprises of aspects like Fitness
function, Continuous Delivery Readiness, Quality
Assurance in the Pipeline, Quantitative and Causal
Analysis, Learning and Development and Team
Culture.
*Research Study (Doctoral Research) on Software Quality Assurance practices in Agile continuous delivery- Anish Cheriyan

11. • Jagdish is the Technical Lead for Tools and Infrastructure at Google GSuite Products.He has 20+ years of expertise
in areas of Product Quality, Test Automation and Faster Releases. His mission is to empower developers with the
tools, practices and testing support to increase their productivity while maintaining high quality standards.Prior
joining Google, he worked at Huawei as Test Engineering Manager.
Jagdish Singh Babra,
Google

12. Data Everywhere...

13. Example #1
Performance Testing Bisection
+
Load Performance Testing
CPU, Memory Profile Diff-
assisted Bisection

14. Ground Rules
● Identify the right metric to measure
● Start with smaller key set of metrics
● Ease of metrics collection (Instrumentation)
● Aggregate metrics to avoid individual bias

15. Interesting Use-cases
● Automatic setup of test stack
● Predict files to modify to fix a bug
● Identify flaky tests
● RPC diff to identify new calls added to the flow

16. • Prasanna is Architect- for the Autonomous Database Cloud Services at Oracle. IN this role he focuses on building next
generation database cloud services targeted at large and critical enterprise workload.
• He has developed and delivered software in the space of communications, middleware and databases which have
had a positive impact in the world.
• He has 20+ patents / multiple international papers and conference presentations. He has developed and architected
commercial telco, IT and cloud products demonstrating high availability (>= 5 9's) + carrier grade (ISSU, real-time
performance, auto-scaling, remote serviceability)
Prasanna Venkatesh,
Oracle

17. From: Wikipedia

18. Challenges for a database cloud service
• Scale
• Even for a single service the scale of operations and development is
phenomenal
• Interdependence of software
• In cloud every service depends on other services. This forms a complex
hierarchy.
• Isolated design and verification is very hard. Leads to lack of determinability
• Database is monolithic and needs to be kept very stable &
deterministic
• Focus on Operations and security

19. What did we do?
• Segregate the architecture into a stable piece releasing in longer
cycles and a agile piece releasing in shorter cycles
• Build resilience into the software
• Autonomous and Layered software
• Agility in response
• Stronger macro processes to ensure coordinated working
• Stronger platforms for continuous delivery
• Complex and powerful monitoring systems

20. What did we do?
• Bake in security into the development process
• Stronger and multiple security checkpoints
• Strong focus on operations
• Work jointly on roadmaps. Ops features part of roadmaps
• Enhanced verification models using staging and approvals from Ops teams

21. Summary
• Due to the scale, velocity and complexity there is a lack of
determinability of software.
• Deal with it by building agility in response and resilience in software
• Agility in response is built by better processes, pipelines and intelligence in
monitoring
• Every piece of software need not be made agile, that is a business-
case dependent decision.

22. System and Software Architect for Embedded and Automotive systems, Amateur Radio Enthusiast
(VU3CIN) and Sailor in training. An electronics and communication engineer who switched to writing
embedded software as a career choice, but keeps in touch with electronics and communication by
making it a hobby.
Sojan James
Harman Automotive

23. Image from: https://www.prnewswire.com/news-releases/simios-8-reasons-to-adopt-industry-4-0--300629039.html
QUALITY 4.0
1784 1870 1969
Quality 4.0

24. Monohull Cruiser
• 5-10 knots
AC72 Hydrofoiling
Catamaran
• Sail faster than the
wind - 44.15 knots (81
km/h) in 15.8 knots of
wind (2.79 times the
wind speed) on July 18,
2013.
AC75 Foiling Monohull
50 Knots (92.6 Km/h)
4-5 Knots

25. X.0 to (X+1).0
• INCREMENTAL INNOVATION
+ =
Electric
Calculator
CREATIVITY
INNOVATION
• Not about slight improvements
• Drastic and fundamental change
• How close to the boundaries we can safely
operate
• How efficient can we be
• Optimization in each and every part of the
system
• Increasing use of technology from other
domains.
Becomes the norm after the initial hurdles

26. QUALITY 4.0
QUALITY IS ENGINEERING
“No problem can be solved from the same level of
consciousness that created it”
Usage of the right technology
Embed Quality at every step
(Impedance Matching)
• Data Science / Machine Learning /
AI
• Modern programming languages
• Formal verification methods
• System Thinking
• Strong engineering foundation
• Quality Processes
• DevOps
• Product Line Thinking
• Agility
1
2

27. Image from: https://www.searchautoparts.com/motorage/electrical/securing-connected-car