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

Bodden, Eric; Hendren, Laurie; Lhoták, Ondřej

doi:10.1007/978-3-540-73589-2_25

Cited by 71 publications

(112 citation statements)

References 21 publications

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“…This deliberately accepted limitation allows for generating highly optimized monitoring code [14]. Although it limits the way of specifying properties, we have been able to write all the properties we considered (including those in [10] and [25]; see, as an example, the property in Figure 2) under this limitation. Moreover, our experience is that a carefully written specification can result in improved monitoring performance.…”

Section: Mop In a Nutshellmentioning

confidence: 99%

Efficient monitoring of parametric context-free patterns

et al. 2010

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Recent developments in runtime verification and monitoring show that parametric regular and temporal logic specifications can be efficiently monitored against large programs. However, these logics reduce to ordinary finite automata, limiting their expressivity. For example, neither can specify structured properties that refer to the call stack of the program. While context-free grammars (CFGs) are expressive and well-understood, existing techniques of monitoring CFGs generate massive runtime overhead in reallife applications. This paper shows for the first time that monitoring parametric CFGs is practical (on the order of 10% or lower for average cases, several times faster than the state-of-the-art). We present a monitor synthesis algorithm for CFGs based on an LR(1) parsing algorithm, modified with stack cloning to account for good prefix matching. In addition, a logic-independent mechanism is introduced to support partial matching, allowing patterns to be checked against fragments of execution traces.

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Section: Mop In a Nutshellmentioning

confidence: 99%

Efficient monitoring of parametric context-free patterns

et al. 2010

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“…The Dependency State Machine defined in the annotation provides Clara with enough domain-specific knowledge to analyze the woven program. The accompanying research paper [17] summarizes Clara's predefined analyses; further details can be found in previous work [10,11,14] and the first author's dissertation [9]. The result is an optimized instrumented program that updates the runtime monitor at fewer locations.…”

Section: Architecture Of Claramentioning

confidence: 99%

“…At ECOOP 2007, we presented a set of three static analyses that attempt to statically optimize tracematches at compile time [14]. The three analyses presented there are similar to the three analysis stages that Clara contains today, however they were all bound to tracematches; they did not generalize to any other monitoring tool.…”

Section: Further Reading On Clara and Its Analysesmentioning

confidence: 99%

“…-The Quick Check in [14] can only detect cases in which a monitor cannot reach a final state as a whole. The improved Quick Check from [11], on the other hand, considers individual paths to final states.…”

Section: Further Reading On Clara and Its Analysesmentioning

confidence: 99%

“…-The Orphan Shadows Analysis in [11] is highly optimized. In [14], the analysis algorithm explicitly enumerated all possible combinations, i.e., subsets of instrumentation points. With 1000 or more points, there can be up to 2 1000 subsets.…”

Section: Further Reading On Clara and Its Analysesmentioning

confidence: 99%

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Clara: Partially Evaluating Runtime Monitors at Compile Time

Bodden

Lam

2010

Runtime Verification

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Abstract. Clara is a novel static-analysis framework for partially evaluating finite-state runtime monitors at compile time. Clara uses static typestate analyses to automatically convert any AspectJ monitoring aspect into a residual runtime monitor that only monitors events triggered by program locations that the analyses failed to prove safe. If the static analysis succeeds on all locations, this gives strong static guarantees. If not, the efficient residual runtime monitor is guaranteed to capture property violations at runtime. Researchers can use Clara with most runtime-monitoring tools that implement monitors as AspectJ aspects.In this tutorial supplement, we provide references to related reading material that will allow the reader to obtain in-depth knowledge about the context in which Clara can be applied and about the techniques that underlie the Clara framework.

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