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

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

Stakeholders of configurable systems are often interested in knowing how configuration
options influence the performance of a system to facilitate, for example, the debugging and …

Almost every complex software system today is configurable. While configurability has many
benefits, it challenges performance prediction, optimization, and debugging. Often, the …

Most software systems provide options that allow users to tailor the system in terms of
functionality and qualities. The increased flexibility raises challenges for understanding the …

Understanding the influence of configuration options on performance is key for finding
optimal system configurations, system understanding, and performance debugging. In prior …

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 …

Configurable software systems provide a multitude of configuration options to adjust and
optimize their functional and non-functional properties. For instance, to find the fastest …

Modeling the performance of a highly configurable software system requires capturing the
influences of its configuration options and their interactions on the system's performance …

Modern software systems often exhibit numerous configuration options to tailor them to user
requirements, including the system's performance behavior. Performance models derived …