Determining whether a configurable software system has a performance bug or it was
misconfigured is often challenging. While there are numerous debugging techniques that …

Deep learning (DL) has been widely applied to many domains. Unique challenges in
engineering DL systems are posed by the programming paradigm shift from traditional …

Software systems introduce an increasing number of configuration options to provide
flexibility, and support updating the options on the fly to provide persistent services. This …

Abstract Context: Software Performance Antipatterns (SPAs) research has focused on
algorithms for their characterization, detection, and solution. Existing algorithms are based …

Automatic configuration tuning helps users who intend to improve software performance.
However, the auto-tuners are limited by the huge configuration search space. More …

Diagnosing a performance bug triggered in production cloud environments is notoriously
challenging. Extracting performance bug signatures can help cloud operators quickly …

Federated learning (FL) is an emerging machine learning paradigm that aims to address the
problem of isolated data islands. To preserve privacy, FL allows machine learning models …

NVMe SSD hugely boosts the I/O speed, with up to GB/s throughput and microsecond-level
latency. Unfortunately, DBMS users can often find their high-performanced storage devices …

Configuration errors are some of the main reasons for software failures. Some configuration
options may even negatively impact the software's security, so that if a user sets the options …

Bug reports, as a frequently consulted software asset, are maintained and evolved in
software communities. A large number of bug reports with complex discussions are …