We propose a sampling infrastructure for gathering information about software from the set of runs experienced by its user community. We show how to gather random samples with very low overhead for users, and we also show how to make use of the information we gather. We present two example applications: sharing the overhead of assertions, and using statistical analysis of a large number of sampled runs to help isolate the location of a bug. 1
A protocol for distributed estimation of discrete distributions is proposed. Each agent begins with ...
Dynamic performance analysis of executing programs commonly relies on statistical profiling techniqu...
International audienceWith the recent bloom of data, there is a huge surge in threats against indivi...
We propose a low-overhead sampling infrastructure for gathering information from the executions expe...
Node sampling services provide peers in a peer-to-peer system with a source of randomly chosen addre...
Representative sampling appears rare in empirical software engineering research. Not all studies nee...
Context: The low quality and small size of samples in empirical studies in software engineering hamp...
Dynamic program analysis encompasses the development of techniques and tools for analyzing computer ...
INST: L_042In data streaming we work with large data from multiple sources. We observe overloaded pa...
One response to the proliferation of large datasets has been to develop ingenious ways to throw reso...
The complexity of modern software makes it difficult to ship correct programs. Errors can cost money...
Populating the testing environment with relevant data represents a great challenge in software valid...
Abstract Tracing mechanisms in distributed systems give important insight into system properties and...
For a large-scale data-intensive environment, such as the World-Wide Web or data warehousing, we oft...
End-user software is executed billions of times daily, but the corresponding execution details (“by-...
A protocol for distributed estimation of discrete distributions is proposed. Each agent begins with ...
Dynamic performance analysis of executing programs commonly relies on statistical profiling techniqu...
International audienceWith the recent bloom of data, there is a huge surge in threats against indivi...
We propose a low-overhead sampling infrastructure for gathering information from the executions expe...
Node sampling services provide peers in a peer-to-peer system with a source of randomly chosen addre...
Representative sampling appears rare in empirical software engineering research. Not all studies nee...
Context: The low quality and small size of samples in empirical studies in software engineering hamp...
Dynamic program analysis encompasses the development of techniques and tools for analyzing computer ...
INST: L_042In data streaming we work with large data from multiple sources. We observe overloaded pa...
One response to the proliferation of large datasets has been to develop ingenious ways to throw reso...
The complexity of modern software makes it difficult to ship correct programs. Errors can cost money...
Populating the testing environment with relevant data represents a great challenge in software valid...
Abstract Tracing mechanisms in distributed systems give important insight into system properties and...
For a large-scale data-intensive environment, such as the World-Wide Web or data warehousing, we oft...
End-user software is executed billions of times daily, but the corresponding execution details (“by-...
A protocol for distributed estimation of discrete distributions is proposed. Each agent begins with ...
Dynamic performance analysis of executing programs commonly relies on statistical profiling techniqu...
International audienceWith the recent bloom of data, there is a huge surge in threats against indivi...