351 research outputs found

    The Paths to Choreography Extraction

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    Choreographies are global descriptions of interactions among concurrent components, most notably used in the settings of verification (e.g., Multiparty Session Types) and synthesis of correct-by-construction software (Choreographic Programming). They require a top-down approach: programmers first write choreographies, and then use them to verify or synthesize their programs. However, most existing software does not come with choreographies yet, which prevents their application. To attack this problem, we propose a novel methodology (called choreography extraction) that, given a set of programs or protocol specifications, automatically constructs a choreography that describes their behavior. The key to our extraction is identifying a set of paths in a graph that represents the symbolic execution of the programs of interest. Our method improves on previous work in several directions: we can now deal with programs that are equipped with a state and internal computation capabilities; time complexity is dramatically better; we capture programs that are correct but not necessarily synchronizable, i.e., they work because they exploit asynchronous communication

    Asymmetric distances for approximate differential privacy

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    Differential privacy is a widely studied notion of privacy for various models of computation, based on measuring differences between probability distributions. We consider (epsilon,delta)-differential privacy in the setting of labelled Markov chains. For a given epsilon, the parameter delta can be captured by a variant of the total variation distance, which we call lv_{alpha} (where alpha = e^{epsilon}). First we study lv_{alpha} directly, showing that it cannot be computed exactly. However, the associated approximation problem turns out to be in PSPACE and #P-hard. Next we introduce a new bisimilarity distance for bounding lv_{alpha} from above, which provides a tighter bound than previously known distances while remaining computable with the same complexity (polynomial time with an NP oracle). We also propose an alternative bound that can be computed in polynomial time. Finally, we illustrate the distances on case studies

    Computing Minimal Distinguishing Hennessy-Milner Formulas is NP-Hard, but Variants are Tractable

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    We study the problem of computing minimal distinguishing formulas for non-bisimilar states in finite LTSs. We show that this is NP-hard if the size of the formula must be minimal. Similarly, the existence of a short distinguishing trace is NP-complete. However, we can provide polynomial algorithms, if minimality is formulated as the minimal number of nested modalities, and it can even be extended by recursively requiring a minimal number of nested negations. A prototype implementation shows that the generated formulas are much smaller than those generated by the method introduced by Cleaveland
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