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Probabilistic programs often trade accuracy for efficiency, and thus may, with a small probability, return an incorrect result. It is important to obtain precise bounds for the probability of these errors, but existing verification…

We present Tachis, a higher-order separation logic to reason about the expected cost of probabilistic programs. Inspired by the uses of time credits for reasoning about the running time of deterministic programs, we introduce a novel notion…

This article presents a type-based analysis for deriving upper bounds on the expected execution cost of probabilistic programs. The analysis is naturally compositional, parametric in the cost model, and supports higher order functions and…

Programming Languages · Computer Science 2020-09-23 Di Wang , David M Kahn , Jan Hoffmann

Properties such as provable security and correctness for randomized programs are naturally expressed relationally as approximate equivalences. As a result, a number of relational program logics have been developed to reason about such…

Logic in Computer Science · Computer Science 2024-12-04 Philipp G. Haselwarter , Kwing Hei Li , Alejandro Aguirre , Simon Oddershede Gregersen , Joseph Tassarotti , Lars Birkedal

We present Coneris, the first higher-order concurrent separation logic for reasoning about error probability bounds of higher-order concurrent probabilistic programs with higher-order state. To support modular reasoning about concurrent…

Logic in Computer Science · Computer Science 2025-08-08 Kwing Hei Li , Alejandro Aguirre , Simon Oddershede Gregersen , Philipp G. Haselwarter , Joseph Tassarotti , Lars Birkedal

We present Foxtrot, the first higher-order separation logic for proving contextual refinement of higher-order concurrent probabilistic programs with higher-order local state. From a high level, Foxtrot inherits various concurrency reasoning…

Logic in Computer Science · Computer Science 2026-04-28 Kwing Hei Li , Alejandro Aguirre , Joseph Tassarotti , Lars Birkedal

We present Polaris, a concurrent separation logic with support for probabilistic reasoning. As part of our logic, we extend the idea of coupling, which underlies recent work on probabilistic relational logics, to the setting of programs…

Programming Languages · Computer Science 2018-11-22 Joseph Tassarotti , Robert Harper

In this work, we study the fully automated inference of expected result values of probabilistic programs in the presence of natural programming constructs such as procedures, local variables and recursion. While crucial, capturing these…

Programming Languages · Computer Science 2023-04-26 Martin Avanzini , Georg Moser , Michael Schaper

Compiler correctness proofs for higher-order concurrent languages are difficult: they involve establishing a termination-preserving refinement between a concurrent high-level source language and an implementation that uses low-level shared…

Programming Languages · Computer Science 2017-01-23 Joseph Tassarotti , Ralf Jung , Robert Harper

We develop a weakest-precondition-style calculus \`a la Dijkstra for reasoning about amortized expected runtimes of randomized algorithms with access to dynamic memory - the $\textsf{aert}$ calculus. Our calculus is truly quantitative, i.e.…

Logic in Computer Science · Computer Science 2022-11-24 Kevin Batz , Benjamin Lucien Kaminski , Joost-Pieter Katoen , Christoph Matheja , Lena Verscht

A typical way of analyzing the time complexity of functional programs is to extract a recurrence expressing the running time of the program in terms of the size of its input, and then to solve the recurrence to obtain a big-O bound. For…

Programming Languages · Computer Science 2020-08-03 Joseph W. Cutler , Daniel R. Licata , Norman Danner

There has recently been exciting progress in the realm of *probabilistic separation logics*. An important subclass of these -- including PSL, Lilac, Bluebell, and pcOL -- are *general-purpose probabilistic logics* (or GPLs, for short),…

Logic in Computer Science · Computer Science 2026-05-14 Janine Lohse , Tim Rohde , Jimmy Xin , Niklas Mück , Iona Kuhn , Derek Dreyer , Deepak Garg , Emanuele D'Osualdo

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle…

Programming Languages · Computer Science 2019-03-26 Peixin Wang , Hongfei Fu , Amir Kafshdar Goharshady , Krishnendu Chatterjee , Xudong Qin , Wenjun Shi

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs.…

Programming Languages · Computer Science 2017-11-27 Van Chan Ngo , Quentin Carbonneaux , Jan Hoffmann

This paper introduces the exponential substitution calculus (ESC), a new presentation of cut elimination for IMELL, based on proof terms and building on the idea that exponentials can be seen as explicit substitutions. The idea in itself is…

Logic in Computer Science · Computer Science 2024-02-14 Beniamino Accattoli

There has been significant progress in understanding the parallelism inherent to iterative sequential algorithms: for many classic algorithms, the depth of the dependence structure is now well understood, and scheduling techniques have been…

Data Structures and Algorithms · Computer Science 2018-08-14 Dan Alistarh , Trevor Brown , Justin Kopinsky , Giorgi Nadiradze

One of the most difficult parts of motion planning in configuration space is ensuring a trajectory does not collide with task-space obstacles in the environment. Generating regions that are convex and collision free in configuration space…

Robotics · Computer Science 2023-03-28 Mark Petersen , Russ Tedrake

We report on intermediate results of our research on reasoning about liveness properties in addition to deep correctness properties for an imperative, concurrent programming language with a higher-order store. At present, we focus on one…

Logic in Computer Science · Computer Science 2023-01-02 Justus Fasse , Bart Jacobs

Most implementations of sampling algorithms for continuous distributions use floating-point numbers, which introduce round-off errors and approximations. These errors can be difficult to analyze, and can cause security issues when used in…

Logic in Computer Science · Computer Science 2026-05-18 Markus de Medeiros , Puming Liu , Kwing Hei Li , Alejandro Aguirre , Lars Birkedal , Joseph Tassarotti

Intensional sets, i.e., sets given by a property rather than by enumerating elements, are widely recognized as a key feature to describe complex problems (see, e.g., specification languages such as B and Z). Notwithstanding, very few tools…

Logic in Computer Science · Computer Science 2019-10-22 Maximiliano Cristiá , Gianfranco Rossi
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