Dependent advice: a general approach to optimizing history-based aspects

Many aspects for runtime monitoring are history-based: they contain pieces of advice that execute conditionally, based on the observed execution history. History-based aspects are notorious for causing high runtime overhead. Compilers can apply powerful optimizations to history-based aspects using domain knowledge. Unfortunately, current aspect languages like AspectJ impede optimizations, as they provide no means to express this domain knowledge. In this paper we present dependent advice, a novel AspectJ language extension. A dependent advice contains dependency annotations that preserve crucial domain knowledge: a dependent advice needs to execute only when its dependencies are fulfilled. Optimizations can exploit this knowledge: we present a whole-program analysis that removes advicedispatch code from program locations at which an advice’s dependencies cannot be fulfilled. Programmers often opt to have history-based aspects generated automatically, from formal specifications fr...

• Type: Conference
• Year: 2009
• Where: AOSD
• Authors: Eric Bodden, Feng Chen, Grigore Rosu
• Keywords: AOSD 2009, Dependent Advice, Domain Knowledge, History-based Aspects, Software Engineering