Modern software applications are adapted to different situations (eg, memory limits,
enabling/disabling features, database credentials) by changing the values of configuration …

There are increasing uses of deep learning (DL) compilers to generate optimized code,
boosting the runtime performance of DL models on specific hardware. Like their traditional …

Highly-configurable systems are such systems which are not developed for single scenario.
However, perhaps they have variable functionality and they are developed for hybrid …

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

DL frameworks are the basis of constructing all DL programs and models, and thus their
bugs could lead to the unexpected behaviors of any DL program or model relying on them …

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 …

The interest in quantum computing is growing, and with it, the importance of software
platforms to develop quantum programs. Ensuring the correctness of such platforms is …

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

Many modern software systems are highly configurable, allowing the user to tune them for
performance and more. Current performance modeling approaches aim at finding …

Configurable software systems can be tuned for better performance. Leveraging on some
Pareto optimizers, recent work has shifted from tuning for a single, time-related performance …