The 7th International Workshop on Testing Database Systems (DBTEST) was held on
June 15th, 2018 in the morning.
within the arrangements of 2018 ACM SIGMOD/PODS to be held in Houston, TX, USA, on June 10th - June 15th, 2018.
News
The presentations of all speakers are available now.
Videos from DBTest are online now on youtube
The workshop programis online.
Keynote: DBTest 2018 will feature a keynote presentation from
Manasi Joshi, Google
Manasi Joshi is a Director of Software Engineering at Google.
She is leading the ML Productivity effort with close collaborations across Tensorflow,
Cloud, Applied Research and product engagement efforts in Google. Prior to this role,
Manasi has a long tenure as an engineering productivity lead in Google’s Display Ads infrastructure team.
on Machine Learning Testing and Productivity
Machine Learning is infused in all walks of life including a lot of Google products such as Google Home,
Search, Gmail, and more, as well as in systems such as those used by self-driving cars and fraud detection systems.
Google is an AI-first company and a tremendous amount of effort is being made to improve people’s experiences using
Google products. However, developing and deploying high-quality, robust ML systems at Google's scale is difficult.
This can be due to many factors including but not limited to distributed ownership, training serving skew,
maintaining privacy and proper access controls of data, model freshness and compatibility.
In the face of such challenges, we started an “ML productivity” effort to empower developers to move
quickly and launch with confidence. This effort encompasses building infrastructure for reliability and
reusability of software as well as extraction of critical ML metrics which can be monitored to make informed
decisions through the ML life cycle. In this talk, we will discuss a few examples where these efforts may be applicable.
Our Sponsors
About DBTEST
With the ever increasing amount of data stored and processed, there is an ongoing need of testing database management systems but also data-intensive systems in general.
Specifically, emerging new technologies such as Non-Volatile Memory impose new challenges (e.g., avoiding persistent memory leaks and partial writes), and novel system
designs including FPGAs, GPUs, and RDMA call for additional attention and sophistication.
Reviving the previous success of the six previous workshops, the goal of DBTest 2017 is to bring researchers and practitioners from academia and industry together to discuss
key problems and ideas related to testing database systems and applications. The long-term objective is to reduce the cost and time required to test and tune data management
and processing products so that users and vendors can spend more time and energy on actual innovations.
The workshop focusses on the following topics:
Testing of database systems, storage services, and database applications
Testing of database systems using novel hardware and software technology (non-volatile memory, hardware transactional memory)
Testing heterogeneous systems with hardware accelerators (GPUs, FPGAs, ASICs, …)
Testing distributed and big data systems
Testing machine learning systems
War stories and lessons learned
Performance and scalability testing
Testing the reliability and availability of database systems
Algorithms and techniques for automatic program verification
Maximizing code coverage during testing of database systems and applications
Generation of synthetic data for test databases
Testing the effectiveness of adaptive policies and components
Tools for analyzing database management systems (e.g., profilers, debuggers)
Workload characterization with respect to performance metrics and engine components
Metrics for test quality, robustness, efficiency, and effectiveness
Operational aspects such as continuous integration and delivery pipelines
Security and vulnerability testing
Paper Submission
Authors are invited to submit original, unpublished research papers that are not being considered for publication in any other forum.
Papers must follow the most recent ACM Proceedings Format.
Papers submitted can be between four and six pages in length, including references and appendix.
2018 ACM SIGMOD/PODS to be held in Houston, TX, USA, 
