Reasoning About Loops Using Vampire in KeY

We describe symbol elimination and consequence finding in the first-order theorem prover Vampire for automatic generation of quantified invariants, possibly with quantifier alternations, of loops with arrays. Unlike the previous implementation of symbol elimination in Vampire, our work is not limited to a specific programming language but provides a generic framework by relying on a simple guarded command representation of the input loop. We also improve the loop analysis part in Vampire by generating loop properties more easily handled by the saturation engine of Vampire. Our experiments show that, with our changes, the number of generated invariants is decreased, in some cases, by a factor of 20. We also provide a framework to use our approach to invariant generation in conjunction with pre- and post-conditions of program loops. We use the program specification to find relevant invariants as well as to verify the partial correctness of the loop. As a case study, we demonstrate how symbol elimination in Vampire can be used as an interface for realistic imperative languages, by integrating our tool in the KeY verification system, thus allowing reasoning about loops in Java programs in a fully automated way, without any user guidance

Four-color flow cytometry bypasses limitations of IG/TCR polymerase chain reaction for minimal residual disease detection in certain subsets of children with acute lymphoblastic leukemia.

International audienceBACKGROUND AND OBJECTIVES: Competitive immunoglobulin/T-cell receptor polymerase-chain reaction (PCR) analysis with fluorescent detection is a rapid, cheap and reproducible method for quantifying minimal residual disease (MRD), which is well adapted to the recognition of high-risk childhood acute lymphoblastic leukemia (ALL). We aimed at defining whether flow cytometry (FC) techniques can bypass limitations of PCR for MRD determination. DESIGN AND METHODS: We analyzed 140 remission samples from 91 patients using both competitive PCR amplification of antigen-receptor genes and four-color FC identification of leukemia immunophenotype. These methods were chosen with the aim of detecting at least 0.1% blasts. RESULTS: MRD was measured using both PCR and FC methods in 123 samples and the two methods provided concordant results in 119 of them (97%). Moreover, three out of the four discordant results appeared minor since MRD was detectable by both methods, but at different levels. In 12 of 13 samples from nine patients, mainly infants with early CD10- and/or t(4;11) B-cell ALL and children with immature T-cell ALL, MRD could be determined using FC whereas PCR failed. Conversely, FC methods were unfeasible due to inappropriate leukemia immunophenotype in three additional children (including two with T-cell ALL) for whom PCR successfully provided MRD results. INTERPRETATION AND CONCLUSIONS: The MRD results provided by FC techniques were highly concordant with those of competitive PCR. Moreover, the applicability of FC appeared higher in certain ALL subsets, although the appropriateness of this technique in terms of outcome prediction remains to be demonstrated

An Inference Rule for the Acyclicity Property of Term Algebras

Term algebras are important structures in many areas of mathematics and computer science. Reasoning about their theories in superposition-based first-order theorem provers is made difficult by the acyclicity property of terms, which is not finitely axiomatizable. We present an inference rule that extends the superposition calculus and allows reasoning about term algebras without axioms to describe the acyclicity property. We detail an indexing technique to efficiently apply this rule in problems containing a large number of clauses. Finally we experimentally evaluate an implementation of this extended calculus in the first-order theorem prover Vampire. The results show that this technique is able to find proofs for difficult problems that existing SMT solvers and first-order theorem provers are unable to solve

Deductive Program Analysis with First-Order Theorem Provers

Software is ubiquitous in nearly all aspects of human life, including safety-critical activities. It is therefore crucial to analyze programs and provide strong guarantees that they perform as expected. Automated theorem provers are increasingly popular tools to assist in this task, as they can be used to automatically discover and prove some semantic properties of programs. This thesis explores new ways to use automated theorem provers for first-order logic in the context of program analysis and verification.Firstly, we present a first-order logic encoding of the semantics of imperative programs containing loops. This encoding can be used to express both functional and temporal properties of loops, and is particularly suited to program analysis with an automated theorem prover. We employ it to automate functional verification, termination analysis and invariant generation for iterative programs operating over arrays.Secondly, we describe how to extend theorems provers based on the superposition calculus to reason about datatypes and codatatypes, which are central to many programs. As the first-order theory of datatypes and codatatypes does not have a finite axiomatization, traditional means to perform theory reasoning in superposition-based provers cannot be used. We overcome this by introducing theory extensions as well as augmenting the superposition calculus with new rules

Loop Analysis by Quantification over Iterations

We present a framework to analyze and verify programs containing loops by using a first-order language of so-called extended expressions. This language can express both functional and temporal properties of loops. We prove soundness and completeness of our framework and use our approach to automate the tasks of partial correctness verification, termination analysis and invariant generation. For doing so, we express the loop semantics as a set of first-order properties over extended expressions and use theorem provers and/or SMT solvers to reason about these properties. Our approach supports full first-order reasoning, including proving program properties with alternation of quantifiers. Our work is implemented in the tool QuIt and successfully evaluated on benchmarks coming from software verification

SMT-Based Planning Synthesis for Distributed System Reconfigurations

International audienceLarge distributed systems with an emphasis on adaptability are now considered a necessity in many domains, yet reconfiguration of these systems is still largely carried out in an ad hoc fashion, a process that is both inefficient and error-prone. In this paper, we tackle the planification problem for the reconfiguration of distributed systems in the component-based reconfiguration model Concerto. Specifically, given some tasks to execute and a desired final state of the system, we show how to compute a reconfiguration plan that guarantees satisfaction of inter-component dependencies and is also optimized for parallel execution. Our technique relies on an SMT solver to compute the required dependencies between components and ultimately schedule the reconfiguration. We illustrate the use of this technique on a variety of synthetic examples as well as a real use case in the context of an OpenStack system

Modélisation et simulation de processus de biologie moléculaire basée sur les réseaux de Pétri : une revue de littérature

Les réseaux de Pétri sont une technique de simulation à événements discrets développée pour la représentation de systèmes et plus particulièrement de leurs propriétés de concurrence et de synchronisation. Différentes extensions à la théorie initiale de cette méthode ont été utilisées pour la modélisation de processus de biologie moléculaire et de réseaux métaboliques. Il s’agit des extensions stochastiques, colorées, hybrides et fonctionnelles. Ce document fait une première revue des différentes approches qui ont été employées et des systèmes biologiques qui ont été modélisés grâce à celles-ci. De plus, le contexte d’application et les objectif s de modélisation de chacune sont discutés

Verified Approximation Algorithms

We present the first formal verification of approximation algorithms for NP-complete optimization problems: vertex cover, independent set, set cover, center selection, load balancing, and bin packing. We uncover incompletenesses in existing proofs and improve the approximation ratio in one case. All proofs are uniformly invariant based

VOC and carbonyl compound emissions of a fiberboard resulting from a coriander biorefinery: comparison with two commercial wood-based building materials

Indoor air quality is a major public health issue. It is related to the choice of construction materials and associated with VOC emissions. Two wood-based commercial panels were tested: a medium-density fiberboard (MDF) and a chipboard (CH), and they were compared to a material produced from a coriander biorefinery (COR). Indicators chosen to compare the materials were physical properties (density, bending properties, surface hardness, thickness swelling, and water absorption) and VOC emissions. Emissions were evaluated in an environmental chamber at 23 °C, 31 °C, and 36 °C, and during 28 days. Carbonyl emissions on day 1 at 23 °C were 74, 146, and 35 μg m−2 h−1, respectively, for MDF, CH, and COR. Terpenic emissions were 12, 185, and 37 μg m−2 h−1, respectively. Higher temperature resulted in higher emissions which decreased over time, except for formaldehyde. VOC emissions depended largely on material and temperature. Formaldehyde emission was 300 to 600 times lower for coriander boards (< 0.2 μg m−2 h−1), making them significantly more environmentally friendly materials in comparison with MDF and chipboard. These results highlight the interest of coriander by-products as raw materials for producing fiberboards with low impact on indoor air quality