Efficient Monitoring of Parametric Context Free Patterns

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 real-life 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

Allen Linear (Interval) Temporal Logic --Translation to LTL and Monitor Synthesis--

The relationship between two well established formalisms for temporal reasoning is first investigated, namely between Allen's interval algebra (or Allen's temporal logic, abbreviated \ATL) and linear temporal logic (\LTL). A discrete variant of \ATL is defined, called Allen linear temporal logic (\ALTL), whose models are \omega-sequences of timepoints, like in \LTL. It is shown that any \ALTL formula can be linearly translated into an equivalent \LTL formula, thus enabling the use of \LTL techniques and tools when requirements are expressed in \ALTL. %This translation also implies the NP-completeness of \ATL satisfiability. Then the monitoring problem for \ALTL is discussed, showing that it is NP-complete despite the fact that the similar problem for \LTL is EXPSPACE-complete. An effective monitoring algorithm for \ALTL is given, which has been implemented and experimented with in the context of planning applications

Distributed Verification of Rare Properties using Importance Splitting Observers

Rare properties remain a challenge for statistical model checking (SMC) due to the quadratic scaling of variance with rarity. We address this with a variance reduction framework based on lightweight importance splitting observers. These expose the model-property automaton to allow the construction of score functions for high performance algorithms. The confidence intervals defined for importance splitting make it appealing for SMC, but optimising its performance in the standard way makes distribution inefficient. We show how it is possible to achieve equivalently good results in less time by distributing simpler algorithms. We first explore the challenges posed by importance splitting and present an algorithm optimised for distribution. We then define a specific bounded time logic that is compiled into memory-efficient observers to monitor executions. Finally, we demonstrate our framework on a number of challenging case studies

Drawing Boundaries for Air Quality Control Under the Clean Air Act: The Importance of NOT Being Nonattainment

Much has changed with regard to air pollution control since 1970 whenCongress revised the Clean Air Act to assume a form that, in very broad terms,it retains today.  From a legal point of view, while states1 still retained at thattime wide-ranging discretion to design the regulatory controls necessary toattain the air quality goals of the Act, that discretion was significantly limitedwhen Congress revisited the Act in 1977.  State discretion diminished to aneven greater extent, particularly with regard to the air pollutants ozone, carbonmonoxide, and particulate matter, when President George H.W. Bush signedthe Clean Air Act Amendments of 1990.</jats:p