Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that …
Many analyses on configurable software systems are intractable when confronted with colossal and highly-constrained configuration spaces. These analyses could instead use …
Detecting and understanding reasons for defects and inadvertent behavior in software is challenging due to their increasing complexity. In configurable software systems, the …
Performance-influence models can help stakeholders understand how and where configuration options and their interactions influence the performance of a system. With this …
Artificial intelligence has gained considerable momentum in software engineering, but there are major challenges that make this domain special. We review recent advances, raise …
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 …
Determining whether a configurable software system has a performance bug or it was misconfigured is often challenging. While there are numerous debugging techniques that …
With large scale and complex configurable systems, it is hard for users to choose the right combination of options (ie, configurations) in order to obtain the wanted trade-off between …
Many modern software systems are highly configurable, allowing the user to tune them for performance and more. Current performance modeling approaches aim at finding …