What is a ‘Good’ Encoding of Guarded Choice?

The pi-calculus with synchronous output and mixed-guarded choices is strictly more expressive than the pi-calculus with asynchronous output and no choice. This result was recently proved by Palamidessi and, as a corollary, she showed that there is no fully compositional encoding from the former into the latter that preserves divergence-freedom and symmetries. This paper argues that there are nevertheless `good' encodings between these calculi. In detail, we present a series of encodings for languages with (1) input-guarded choice, (2) both input- and output-guarded choice, and (3) mixed-guarded choice, and investigate them with respect to compositionality and divergence-freedom. The first and second encoding satisfy all of the above criteria, but various `good' candidates for the third encoding - inspired by an existing distributed implementation - invalidate one or the other criterion. While essentially confirming Palamidessi's result, our study suggests that the combination of strong compositionality and divergence-freedom is too strong for more practical purposes

What Is a ‘Good’ Encoding of Guarded Choice?

The pi-calculus with synchronous output and mixed-guarded choices is strictly more expressive than the pi-calculus with asynchronous output and no choice. As a corollary, Palamidessi recently proved that there is no fully compositional encodingfrom the former into the latter that preserves divergence-freedom and symmetries. This paper shows that there are nevertheless `good' encodings between these calculi.In detail, we present a series of encodings for languages with (1) input-guarded choice, (2) both input- and output-guarded choice, and (3) mixed-guarded choice, and investigate them with respect to compositionality and divergence-freedom. The firstand second encoding satisfy all of the above criteria, but various `good' candidates for the third encoding - inspired by an existing distributed implementation - invalidate one or the other criterion. While essentially confirming Palamidessi's result, our studysuggests that the combination of strong compositionality and divergence-freedom is too strong for more practical purposes

On the expressiveness of mixed choice sessions

Session types provide a flexible programming style for structuring interaction, and are used to guarantee a safe and consistent composition of distributed processes. Traditional session types include only one-directional input (external) and output (internal) guarded choices. This prevents the session-processes to explore the full expressive power of the pi-calculus where the mixed choices are proved more expressive than the (non-mixed) guarded choices. To account this issue, recently Casal, Mordido, and Vasconcelos proposed the binary session types with mixed choices (CMV+). This paper carries a surprising, unfortunate result on CMV+: in spite of an inclusion of unrestricted channels with mixed choice, CMV+'s mixed choice is rather separate and not mixed. We prove this negative result using two methodologies (using either the leader election problem or a synchronisation pattern as distinguishing feature), showing that there exists no good encoding from the pi-calculus into CMV+, preserving distribution. We then close their open problem on the encoding from CMV+ into CMV (without mixed choice), proving its soundness and thereby that the encoding is good up to coupled similarity

Infinitary λ\lambda-Calculi from a Linear Perspective (Long Version)

We introduce a linear infinitary $\lambda$-calculus, called $\ell\Lambda_{\infty}$, in which two exponential modalities are available, the first one being the usual, finitary one, the other being the only construct interpreted coinductively. The obtained calculus embeds the infinitary applicative $\lambda$-calculus and is universal for computations over infinite strings. What is particularly interesting about $\ell\Lambda_{\infty}$, is that the refinement induced by linear logic allows to restrict both modalities so as to get calculi which are terminating inductively and productive coinductively. We exemplify this idea by analysing a fragment of $\ell\Lambda$ built around the principles of $\mathsf{SLL}$ and $\mathsf{4LL}$. Interestingly, it enjoys confluence, contrarily to what happens in ordinary infinitary $\lambda$-calculi

Breaking Symmetries

A well-known result by Palamidessi tells us that {\pi}mix (the {\pi}-calculus with mixed choice) is more expressive than {\pi}sep (its subset with only separate choice). The proof of this result argues with their different expressive power concerning leader election in symmetric networks. Later on, Gorla of- fered an arguably simpler proof that, instead of leader election in symmetric networks, employed the reducibility of "incestual" processes (mixed choices that include both enabled senders and receivers for the same channel) when running two copies in parallel. In both proofs, the role of breaking (ini- tial) symmetries is more or less apparent. In this paper, we shed more light on this role by re-proving the above result-based on a proper formalization of what it means to break symmetries-without referring to another layer of the distinguishing problem domain of leader election. Both Palamidessi and Gorla rephrased their results by stating that there is no uniform and reason- able encoding from {\pi}mix into {\pi}sep . We indicate how the respective proofs can be adapted and exhibit the consequences of varying notions of uniformity and reasonableness. In each case, the ability to break initial symmetries turns out to be essential

Full abstraction for expressiveness: history, myths and facts

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.What does it mean that an encoding is fully abstract? What does it not mean? In this position paper, we want to help the reader to evaluate the real benefits of using such a notion when studying the expressiveness of programming languages. Several examples and counterexamples are given. In some cases, we work at a very abstract level; in other cases, we give concrete samples taken from the field of process calculi, where the theory of expressiveness has been mostly developed in the last years

Decoding Choice Encodings

We study two encodings of the asynchronous pi-calculus with input-guarded choice into its choice-free fragment. One encoding is divergence-free, but refines the atomic commitment of choice into gradual commitment. The other preserves atomicity, but introduces divergence. The divergent encoding is fully abstract with respect to weak bisimulation, but the more natural divergence-free encoding is not. Instead, we show that it is fully abstract with respect to coupled simulation, a slightly coarser - but still coinductively defined - equivalence that does not enforce bisimilarity of internal branching decisions. The correctness proofs for the two choice encodings introduce a novel proof technique exploiting the properties of explicit decodings from translations to source terms

Making the Most of Your Samples

We study the problem of setting a price for a potential buyer with a valuation drawn from an unknown distribution $D$. The seller has "data"' about $D$ in the form of $m \ge 1$ i.i.d. samples, and the algorithmic challenge is to use these samples to obtain expected revenue as close as possible to what could be achieved with advance knowledge of $D$. Our first set of results quantifies the number of samples $m$ that are necessary and sufficient to obtain a $(1-\epsilon)$-approximation. For example, for an unknown distribution that satisfies the monotone hazard rate (MHR) condition, we prove that $\tilde{\Theta}(\epsilon^{-3/2})$ samples are necessary and sufficient. Remarkably, this is fewer samples than is necessary to accurately estimate the expected revenue obtained by even a single reserve price. We also prove essentially tight sample complexity bounds for regular distributions, bounded-support distributions, and a wide class of irregular distributions. Our lower bound approach borrows tools from differential privacy and information theory, and we believe it could find further applications in auction theory. Our second set of results considers the single-sample case. For regular distributions, we prove that no pricing strategy is better than $\tfrac{1}{2}$-approximate, and this is optimal by the Bulow-Klemperer theorem. For MHR distributions, we show how to do better: we give a simple pricing strategy that guarantees expected revenue at least $0.589$ times the maximum possible. We also prove that no pricing strategy achieves an approximation guarantee better than $\frac{e}{4} \approx .68$