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Sound Concurrent Traces for Online Monitoring

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Model Checking Software (SPIN 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13872))

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Abstract

Monitoring concurrent programs typically rely on collecting traces to abstract program executions. However, existing approaches targeting general behavioral properties are either not tailored for online monitoring, are no longer maintained, or implement naive instrumentation that often leads to unsound verdicts. We first define the notion of when a trace is representative of a concurrent execution. We then present a non-blocking vector clock algorithm to collect sound concurrent traces on the fly reflecting the partial order between events. Moreover, concurrent events in the representative trace pose a soundness problem for monitors synthesized from total order formalisms. For this, we extract a causal dependence relation from the monitor to check if the trace has the needed orderings and define the conditions to decide at runtime when a collected trace is monitorable. We implement our contributions in a tool, FACTS, which instruments programs compiling to Java bytecode, constructs sound representative traces, and warns the monitor about non-monitorable traces. We evaluate our work and compare it with existing approaches.

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Notes

  1. 1.

    The algorithm might miss, in some marginal cases, ordering information resulting in sound but unfaithful traces (see Sect. 5).

  2. 2.

    Such as \(\texttt{synchronized}\) in Java.

  3. 3.

    We depict actions using the notation \(\mathtt {id.label^{tid}_{resource}}\) in diagrams.

  4. 4.

    We assume familiarity with partial orders and partially ordered sets.

  5. 5.

    We omit some null checks to simplify the presentation of the algorithm, however, assume that joining \(e. VC \) with a null value does not affect it.

  6. 6.

    Atomic operations such as compare-and-swap are handled differently since we check for the result of the operation before emitting an action.

  7. 7.

    In the technical report [68], we extract \(\mathcal {I}_D\) from 55 event-based property specifications from [1, 24] written as Quantified Regular Expressions (QREs).

  8. 8.

    Implementation details can be found in the technical report [68].

  9. 9.

    We also collect linear traces as collected by Java-MOP [21] and show the number of ordering corrections made with concurrent traces, details in [68].

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  1. Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, 38000, Grenoble, France

    Chukri Soueidi & Yliès Falcone

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    Georgiana Caltais

  2. Aalborg University, Aalborg, Denmark

    Christian Schilling

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Soueidi, C., Falcone, Y. (2023). Sound Concurrent Traces for Online Monitoring. In: Caltais, G., Schilling, C. (eds) Model Checking Software. SPIN 2023. Lecture Notes in Computer Science, vol 13872. Springer, Cham. https://doi.org/10.1007/978-3-031-32157-3_4

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