| Profile:
Sudip
Naha has over 9 years of experience in product
testing and project life cycle management. He is currently
heading the Testing Academy, an organizational initiative,
from R&D services division of MindTree. In this
role, his responsibilities include ownership of intellectual
property development, team competency development and
test process improvement. He has Lead and managed projects
involving feature verification, protocol compliance,
devices and subsystems validation and application testing
in Telecommunications, Data communications, Enterprise
Web application and Storage domains. He also has hands-on
experience in design and implementation of test automation
frameworks.
Shalaka
Dani has over 12 years of experience in application
and system testing and project life cycle management.
She is currently heading the Testing Academy, an organizational
initiative, from IT services division of MindTree. In
this role, her responsibilities include ownership of
intellectual property development. She has Lead and
managed very large teams in Travel & Transportation
and Telecom domain. She had successfully undertaken
key initiatives for MindTree such as Test process implementation
and improvement, development of performance testing,
technologies, Domain and Service based framework
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Abstract
:
Today’s
systems or business enabling solutions run non-stop for years
without fault. The recovery is expected automatically with
no losses. When such is the expectation from these systems/products,
quality cannot be compromised.
Given
such complex systems, test coverage has always been a challenge.
It is assume that testing team would quickly design quality
test cases to ensure better test coverage in a given time
and cost. These test cases are expected to execute various
usage paths, validate all possible triggers and their corresponding
effects to determine critical features such predictability,
reliability, usability and timeliness in responses.
Formal
techniques that have evolved over the years, like Cause-effect
graphing and State-Transition modelling, can help address
these challenges. These techniques are used to uncover Requirement
gaps, Design defects in the early stages of system/product
development.
In
this paper/tutorial we will demonstrate the tool/technique
of Cause-Effect Graph – Boolean operator (CEG-BOR) that
is based on propositional logic representation of the functional
specifications. We will share our knowledge and experience
in a toolkit for handling the analysis and data management
necessary to apply Model-Based Statistical Testing.
[In Paper, Case studies will be discussed, which describes
the application of these techniques and the tools that enable
their usage in an effective manner.]
[In this tutorial, participants would get hands-on experience
of application of these techniques and the tools that enable
their usage in an effective manner.]
Key takeaways include knowledge of methods for
1. Better product understanding
2. Better traceability to requirements
3. Approach and Techniques to automate test cases
4. Estimation of test execution effort
5. Optimization of test effort
6. Predictable system/product quality
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