Recently, we have been witnessing a rapid increase in the use of machine learning
techniques in self-adaptive systems. Machine learning has been used for a variety of …

Performance is arguably the most crucial attribute that reflects the quality of a configurable
software system. However, given the increasing scale and complexity of modern software …

High throughput experimentation in heterogeneous catalysis provides an efficient solution to
the generation of large datasets under reproducible conditions. Knowledge extraction from …

Performance-influence models can help stakeholders understand how and where
configuration options and their interactions influence the performance of a system. With this …

When tuning software configuration for better performance (eg, latency or throughput), an
important issue that many optimizers face is the presence of local optimum traps …

Modern computer systems are highly configurable, with the total variability space sometimes
larger than the number of atoms in the universe. Understanding and reasoning about the …

Most modern software systems (operating systems like Linux or Android, Web browsers like
Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications …

Numerous software systems are highly configurable and provide a myriad of configuration
options that users can tune to fit their functional and performance requirements (eg …

Machine/deep learning models have been widely adopted to predict the configuration
performance of software systems. However, a crucial yet unaddressed challenge is how to …

Learning and predicting the performance of given software configurations are of high
importance to many software engineering activities. While configurable software systems will …