Albert-Jan van Blaaderen
Squerist (the Netherlands)
Effective probes to measure your test data
During this session I will discuss the benefits of integrating test data integrity monitoring in your ci/cd deployment implementation pipeline.
I will argue and motivate that in order to make a correct assessment of the validity of information retrieved from monitoring sources continuous validation of data integrity is required. Another topic involves the question whether or not search-based software engineering (SBSE) methods can (re)-position test probes to identify data integrity issues.
Together we will look at cases where problem-specific fitness functions can find optimal matching test data references to be used in a risk-based test approach from a potentially infinite number of data sources.
This session will take a pragmatic and empiric angle to address multiple qualitative statements regarding the hypothetical system state of the software under test based on information obtained from various monitoring/analytic sources that are commonly in place within an enterprise level IT landscape in 2020.
You will learn:
• how (infrastructure) testing probes can support a data-driven risk-based test strategy
• apply data that contributes to your adaptive testing strategy by recognizing and correlating deviations and anomalies
• new perspectives on data quality / data integrity
• new ways to improve your data quality monitoring
Having previously worked worked as an IT administrator and part-time software developer he started his professional test career in 2002 and subsequently worked in test management and principal technology roles at various employers.
He considers testing a great way to explore new technology and has been able to apply his testing skills within software development, cloud engineering and digital forensics.
His most recent assignments involve cloud technology, advanced analytics and infrastructure as code. As of 2016 he enjoys providing expert consultancy services at Squerist addressing testing challenges with a strong emphasis on novel technology, empirical validation, smart analytics and operational control.