A Staged Static Program Analysis to Improve the Performance of Runtime Monitoring

In runtime monitoring, a programmer specifies a piece of code to execute when a trace of events occurs during program execution. Our work is based on tracematches, an extension to AspectJ, which allows programmers to specify traces via regular expressions with free variables. In this paper we present a staged static analysis which speeds up trace matching by reducing the required runtime instrumentation. The first stage is a simple analysis that rules out entire tracematches, just based on the names of symbols. In the second stage, a points-to analysis is used, along with a flow-insensitive analysis that eliminates instrumentation points with inconsistent variable bindings. In the third stage the points-to analysis is combined with a flow-sensitive analysis that also takes into consideration the order in which the symbols may execute. To examine the effectiveness of each stage, we experimented with a set of nine tracematches applied to the DaCapo benchmark suite. We found that about 25% of the tracematch/benchmark combinations had instrumentation overheads greater than 10%. In these cases the first two stages work well for certain classes of tracematches, often leading to significant performance improvements. Somewhat surprisingly, we found the third, flow-sensitive, stage did not add any improvements.