149 research outputs found
Stochastic Invariants for Probabilistic Termination
Termination is one of the basic liveness properties, and we study the
termination problem for probabilistic programs with real-valued variables.
Previous works focused on the qualitative problem that asks whether an input
program terminates with probability~1 (almost-sure termination). A powerful
approach for this qualitative problem is the notion of ranking supermartingales
with respect to a given set of invariants. The quantitative problem
(probabilistic termination) asks for bounds on the termination probability. A
fundamental and conceptual drawback of the existing approaches to address
probabilistic termination is that even though the supermartingales consider the
probabilistic behavior of the programs, the invariants are obtained completely
ignoring the probabilistic aspect.
In this work we address the probabilistic termination problem for
linear-arithmetic probabilistic programs with nondeterminism. We define the
notion of {\em stochastic invariants}, which are constraints along with a
probability bound that the constraints hold. We introduce a concept of {\em
repulsing supermartingales}. First, we show that repulsing supermartingales can
be used to obtain bounds on the probability of the stochastic invariants.
Second, we show the effectiveness of repulsing supermartingales in the
following three ways: (1)~With a combination of ranking and repulsing
supermartingales we can compute lower bounds on the probability of termination;
(2)~repulsing supermartingales provide witnesses for refutation of almost-sure
termination; and (3)~with a combination of ranking and repulsing
supermartingales we can establish persistence properties of probabilistic
programs.
We also present results on related computational problems and an experimental
evaluation of our approach on academic examples.Comment: Full version of a paper published at POPL 2017. 20 page
Quantitative Regular Expressions for Arrhythmia Detection Algorithms
Motivated by the problem of verifying the correctness of arrhythmia-detection
algorithms, we present a formalization of these algorithms in the language of
Quantitative Regular Expressions. QREs are a flexible formal language for
specifying complex numerical queries over data streams, with provable runtime
and memory consumption guarantees. The medical-device algorithms of interest
include peak detection (where a peak in a cardiac signal indicates a heartbeat)
and various discriminators, each of which uses a feature of the cardiac signal
to distinguish fatal from non-fatal arrhythmias. Expressing these algorithms'
desired output in current temporal logics, and implementing them via monitor
synthesis, is cumbersome, error-prone, computationally expensive, and sometimes
infeasible.
In contrast, we show that a range of peak detectors (in both the time and
wavelet domains) and various discriminators at the heart of today's
arrhythmia-detection devices are easily expressible in QREs. The fact that one
formalism (QREs) is used to describe the desired end-to-end operation of an
arrhythmia detector opens the way to formal analysis and rigorous testing of
these detectors' correctness and performance. Such analysis could alleviate the
regulatory burden on device developers when modifying their algorithms. The
performance of the peak-detection QREs is demonstrated by running them on real
patient data, on which they yield results on par with those provided by a
cardiologist.Comment: CMSB 2017: 15th Conference on Computational Methods for Systems
Biolog
Counterexample-Guided Polynomial Loop Invariant Generation by Lagrange Interpolation
We apply multivariate Lagrange interpolation to synthesize polynomial
quantitative loop invariants for probabilistic programs. We reduce the
computation of an quantitative loop invariant to solving constraints over
program variables and unknown coefficients. Lagrange interpolation allows us to
find constraints with less unknown coefficients. Counterexample-guided
refinement furthermore generates linear constraints that pinpoint the desired
quantitative invariants. We evaluate our technique by several case studies with
polynomial quantitative loop invariants in the experiments
PrIC3: Property Directed Reachability for MDPs
IC3 has been a leap forward in symbolic model checking. This paper proposes
PrIC3 (pronounced pricy-three), a conservative extension of IC3 to symbolic
model checking of MDPs. Our main focus is to develop the theory underlying
PrIC3. Alongside, we present a first implementation of PrIC3 including the key
ingredients from IC3 such as generalization, repushing, and propagation
Non-polynomial Worst-Case Analysis of Recursive Programs
We study the problem of developing efficient approaches for proving
worst-case bounds of non-deterministic recursive programs. Ranking functions
are sound and complete for proving termination and worst-case bounds of
nonrecursive programs. First, we apply ranking functions to recursion,
resulting in measure functions. We show that measure functions provide a sound
and complete approach to prove worst-case bounds of non-deterministic recursive
programs. Our second contribution is the synthesis of measure functions in
nonpolynomial forms. We show that non-polynomial measure functions with
logarithm and exponentiation can be synthesized through abstraction of
logarithmic or exponentiation terms, Farkas' Lemma, and Handelman's Theorem
using linear programming. While previous methods obtain worst-case polynomial
bounds, our approach can synthesize bounds of the form
as well as where is not an integer. We present
experimental results to demonstrate that our approach can obtain efficiently
worst-case bounds of classical recursive algorithms such as (i) Merge-Sort, the
divide-and-conquer algorithm for the Closest-Pair problem, where we obtain
worst-case bound, and (ii) Karatsuba's algorithm for
polynomial multiplication and Strassen's algorithm for matrix multiplication,
where we obtain bound such that is not an integer and
close to the best-known bounds for the respective algorithms.Comment: 54 Pages, Full Version to CAV 201
The complex TIE between macrophages and angiogenesis
Macrophages are primarily known as phagocytic immune cells, but they also play a role in diverse processes, such as morphogenesis, homeostasis and regeneration. In this review, we discuss the influence of macrophages on angiogenesis, the process of new blood vessel formation from the pre-existing vasculature. Macrophages play crucial roles at each step of the angiogenic cascade, starting from new blood vessel sprouting to the remodelling of the vascular plexus and vessel maturation. Macrophages form promising targets for both pro- and anti-angiogenic treatments. However, to target macrophages, we will first need to understand the mechanisms that control the functional plasticity of macrophages during each of the steps of the angiogenic cascade. Here, we review recent insights in this topic. Special attention will be given to the TIE2-expressing macrophage (TEM), which is a subtype of highly angiogenic macrophages that is able to influence angiogenesis via the angiopoietin-TIE pathway
Antioxidant Machinery Differs between Melanic and Light Nestlings of Two Polymorphic Raptors
Colour polymorphism results from the expression of multiallelic genes generating phenotypes with very distinctive colourations. Most colour polymorphisms are due to differences in the type or amount of melanins present in each morph, which also differ in several behavioural, morphometric and physiological attributes. Melanin-based colour morphs could also differ in the levels of glutathione (GSH), a key intracellular antioxidant, because of the role of this molecule in melanogenesis. As GSH inhibits the synthesis of eumelanin (i.e. the darkest melanin form), individuals of darker morphs are expected to have lower GSH levels than those of lighter morphs. We tested this prediction in nestlings of two polymorphic raptors, the booted eagle Hieraaetus pennatus and the Eleonora's falcon Falco eleonorae, both of which occur in two morphs differing in the extent of eumelanic plumage. As expected, melanic booted eagle nestlings had lower blood GSH levels than light morph eagle nestlings. In the Eleonora's falcon, however, melanic nestlings only had lower GSH levels after controlling for the levels of other antioxidants. We also found that melanic female eagle nestlings had higher levels of antioxidants other than GSH and were in better body condition than light female eagle nestlings. These findings suggest an adaptive response of melanic nestlings to compensate for reduced GSH levels. Nevertheless, these associations were not found in falcons, indicating species-specific particularities in antioxidant machinery. Our results are consistent with previous work revealing the importance of GSH on the expression of melanic characters that show continuous variation, and suggest that this pathway also applies to discrete colour morphs. We suggest that the need to maintain low GSH levels for eumelanogenesis in dark morph individuals may represent a physiological constraint that helps regulate the evolution and maintenance of polymorphisms
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